Ai generator.
Research terms are specific words or phrases used in academic writing to describe the research process, methodologies, and findings. These include concepts like hypothesis , variables, sample size, literature review, and data analysis. Understanding these terms is crucial for interpreting research studies and effectively communicating ideas. Mastery of research terms enhances clarity in academic discourse, whether in a research project proposal , a qualitative research report , or the description of research methodology.
Terms in research refer to the specific words, phrases, and concepts used within a study to define its scope, methodology , and focus. These terms ensure clarity and precision, allowing researchers to communicate ideas and findings effectively. Clear definitions facilitate a shared understanding and maintain the integrity and replicability of research.
Sampling Bias | Control Variable |
Research Design | Data Analysis |
Primary Data | Secondary Data |
Theoretical Sampling | Purposive Sampling |
Snowball Sampling | Cluster Sampling |
Stratified Sampling | Survey |
Questionnaire | Interview |
Focus Group | Field Study |
Experimental Design | Randomized Controlled Trial (RCT) |
Ethnography | Grounded Theory |
Content Analysis | Descriptive Research |
Explanatory Research | Exploratory Research |
Mixed Methods | Triangulation |
Hypothesis Testing | Null Hypothesis |
Alternative Hypothesis | Research Proposal |
1. abstract.
Investigation | Study |
Inquiry | Examination |
Analysis | Exploration |
Survey | Experiment |
Probe | Scrutiny |
Inspection | Review |
Evaluation | Assessment |
Observation | Fieldwork |
Appraisal | Exploration |
Audit | Dissection |
What is a variable in research.
A variable is any characteristic, number, or quantity that can be measured or quantified in research.
Qualitative research explores concepts and experiences in-depth, while quantitative research involves measuring and analyzing numerical data.
A literature review summarizes existing research on a topic, identifying trends, gaps, and key findings.
A sample is a subset of a population selected for study to represent the entire group.
A hypothesis is a testable prediction or educated guess about the relationship between two or more variables in a study.
Data collection involves gathering information from various sources to address a research question or hypothesis.
An independent variable is the variable that is manipulated or changed in an experiment to observe its effect.
A dependent variable is the variable being tested and measured in an experiment, affected by the independent variable.
A control group is a group in an experiment that does not receive the treatment, used for comparison against the experimental group.
Research methodology is the systematic plan for conducting research, including methods for data collection and analysis.
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Home » Research Paper – Structure, Examples and Writing Guide
Table of Contents
Definition:
Research Paper is a written document that presents the author’s original research, analysis, and interpretation of a specific topic or issue.
It is typically based on Empirical Evidence, and may involve qualitative or quantitative research methods, or a combination of both. The purpose of a research paper is to contribute new knowledge or insights to a particular field of study, and to demonstrate the author’s understanding of the existing literature and theories related to the topic.
The structure of a research paper typically follows a standard format, consisting of several sections that convey specific information about the research study. The following is a detailed explanation of the structure of a research paper:
The title page contains the title of the paper, the name(s) of the author(s), and the affiliation(s) of the author(s). It also includes the date of submission and possibly, the name of the journal or conference where the paper is to be published.
The abstract is a brief summary of the research paper, typically ranging from 100 to 250 words. It should include the research question, the methods used, the key findings, and the implications of the results. The abstract should be written in a concise and clear manner to allow readers to quickly grasp the essence of the research.
The introduction section of a research paper provides background information about the research problem, the research question, and the research objectives. It also outlines the significance of the research, the research gap that it aims to fill, and the approach taken to address the research question. Finally, the introduction section ends with a clear statement of the research hypothesis or research question.
The literature review section of a research paper provides an overview of the existing literature on the topic of study. It includes a critical analysis and synthesis of the literature, highlighting the key concepts, themes, and debates. The literature review should also demonstrate the research gap and how the current study seeks to address it.
The methods section of a research paper describes the research design, the sample selection, the data collection and analysis procedures, and the statistical methods used to analyze the data. This section should provide sufficient detail for other researchers to replicate the study.
The results section presents the findings of the research, using tables, graphs, and figures to illustrate the data. The findings should be presented in a clear and concise manner, with reference to the research question and hypothesis.
The discussion section of a research paper interprets the findings and discusses their implications for the research question, the literature review, and the field of study. It should also address the limitations of the study and suggest future research directions.
The conclusion section summarizes the main findings of the study, restates the research question and hypothesis, and provides a final reflection on the significance of the research.
The references section provides a list of all the sources cited in the paper, following a specific citation style such as APA, MLA or Chicago.
You can write Research Paper by the following guide:
Note : The below example research paper is for illustrative purposes only and is not an actual research paper. Actual research papers may have different structures, contents, and formats depending on the field of study, research question, data collection and analysis methods, and other factors. Students should always consult with their professors or supervisors for specific guidelines and expectations for their research papers.
Research Paper Example sample for Students:
Title: The Impact of Social Media on Mental Health among Young Adults
Abstract: This study aims to investigate the impact of social media use on the mental health of young adults. A literature review was conducted to examine the existing research on the topic. A survey was then administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO (Fear of Missing Out) are significant predictors of mental health problems among young adults.
Introduction: Social media has become an integral part of modern life, particularly among young adults. While social media has many benefits, including increased communication and social connectivity, it has also been associated with negative outcomes, such as addiction, cyberbullying, and mental health problems. This study aims to investigate the impact of social media use on the mental health of young adults.
Literature Review: The literature review highlights the existing research on the impact of social media use on mental health. The review shows that social media use is associated with depression, anxiety, stress, and other mental health problems. The review also identifies the factors that contribute to the negative impact of social media, including social comparison, cyberbullying, and FOMO.
Methods : A survey was administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The survey included questions on social media use, mental health status (measured using the DASS-21), and perceived impact of social media on their mental health. Data were analyzed using descriptive statistics and regression analysis.
Results : The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO are significant predictors of mental health problems among young adults.
Discussion : The study’s findings suggest that social media use has a negative impact on the mental health of young adults. The study highlights the need for interventions that address the factors contributing to the negative impact of social media, such as social comparison, cyberbullying, and FOMO.
Conclusion : In conclusion, social media use has a significant impact on the mental health of young adults. The study’s findings underscore the need for interventions that promote healthy social media use and address the negative outcomes associated with social media use. Future research can explore the effectiveness of interventions aimed at reducing the negative impact of social media on mental health. Additionally, longitudinal studies can investigate the long-term effects of social media use on mental health.
Limitations : The study has some limitations, including the use of self-report measures and a cross-sectional design. The use of self-report measures may result in biased responses, and a cross-sectional design limits the ability to establish causality.
Implications: The study’s findings have implications for mental health professionals, educators, and policymakers. Mental health professionals can use the findings to develop interventions that address the negative impact of social media use on mental health. Educators can incorporate social media literacy into their curriculum to promote healthy social media use among young adults. Policymakers can use the findings to develop policies that protect young adults from the negative outcomes associated with social media use.
References :
Appendix : The survey used in this study is provided below.
Social Media and Mental Health Survey
Thank you for your participation!
Research papers have several applications in various fields, including:
Research papers are typically written when a person has completed a research project or when they have conducted a study and have obtained data or findings that they want to share with the academic or professional community. Research papers are usually written in academic settings, such as universities, but they can also be written in professional settings, such as research organizations, government agencies, or private companies.
Here are some common situations where a person might need to write a research paper:
The purpose of a research paper is to present the results of a study or investigation in a clear, concise, and structured manner. Research papers are written to communicate new knowledge, ideas, or findings to a specific audience, such as researchers, scholars, practitioners, or policymakers. The primary purposes of a research paper are:
Research papers have several characteristics that distinguish them from other forms of academic or professional writing. Here are some common characteristics of research papers:
Research papers have many advantages, both for the individual researcher and for the broader academic and professional community. Here are some advantages of research papers:
Research papers also have some limitations that should be considered when interpreting their findings or implications. Here are some common limitations of research papers:
Researcher, Academic Writer, Web developer
Table of contents:-, research report meaning, characteristics of good research report, key characteristics of research report, types of research report, stages in preparation of research report, characteristics of a good report.
A research report is a document that conveys the outcomes of a study or investigation. Its purpose is to communicate the research’s findings, conclusions, and implications to a particular audience. This report aims to offer a comprehensive and unbiased overview of the research process, methodology, and results.
Once the researcher has completed data collection , data processing, developing and testing hypotheses, and interpretation of responses, the next important phase in research is the preparation of the research report. A research report is essential for the communication of research findings to its potential users.
The research report must be free from personal bias, external influences, and subjective factors. i.e., it must be free from one’s liking and disliking. The research report must be prepared to meet impersonal needs.
According to Lancaster, “A report is a statement of collected and considered facts, so drawn-ups to give clear and concise information to persons who are not already in possession of the full facts of the subject matter of the report”.
When researchers communicate their results in writing, they create a research report. It includes the research methodology, approaches, data collection precautions, research findings, and recommendations for solving related problems. Managers can put this result into action for more effective decision making .
Generally, top management places a higher emphasis on obtaining the research outcome rather than delving into the research procedure. Hence, the research report acts as a presentation that highlights the procedure and methodology adopted by the researcher.
The research report presents the complete procedure in a comprehensive way that in turn helps the management in making crucial decisions. Creating a research report adheres to a specific format, sequence, and writing style.
Enhance the effectiveness of a research report by incorporating various charts, graphs, diagrams, tables, etc. By using different representation techniques, researchers can convince the audience as well as the management in an effective way.
Characteristics of a good research report are listed below:
The following paragraphs outline the characteristics of a good research report.
Report information must be accurate and based on facts, credible sources and data to establish reliability and trustworthiness. It should not be biased by the personal feelings of the writer. The information presented must be as precise as possible.
The language of a research report should be as simple as possible to ensure easy understanding. A good report communicates its message clearly and without ambiguity through its language.
It is a document of practical utility; therefore, it should be grammatically accurate, brief, and easily understood.
Jargon and technical words should be avoided when writing the report. Even in a technical report, there should be restricted use of technical terms if it is to be presented to laymen.
The report must be straightforward, lucid, and comprehensive in every aspect. Ambiguity should be avoided at all costs. Clarity is achieved through the strategic and practical organization of information. Report writers should divide their report into short paragraphs with headings and insert other suitable signposts to enhance clarity. They should:
A report should concisely convey the key points without unnecessary length, ensuring that the reader’s patience is not lost and ideas are not confused. Many times, people lack the time to read lengthy reports.
However, a report must also be complete. Sometimes, it is important to have a detailed discussion about the facts. A report is not an essay; therefore, points should be added to it.
A report requires a visually appealing presentation and, whenever feasible, should be attention-grabbing. An effective report depends on the arrangement, organization, format, layout, typography, printing quality, and paper choice. Big companies often produce very attractive and colourful Annual Reports to showcase their achievements and financial performance.
Reports should be clear and straightforward for easy understanding. The style of presentation and the choice of words should be attractive to readers. The writer must present the facts in elegant and grammatically correct English so that the reader is compelled to read the report from beginning to end.
Only then does a report serve its purpose. A report written by different individuals on the same subject matter can vary depending on the intended audience.
Reports should be reliable and should not create an erroneous impression in the minds of readers due to oversight or neglect. The facts presented in a report should be pertinent.
Every fact in a report must align with the central purpose, but it is also vital to ensure that all pertinent information is included.
Irrelevant facts can make a report confusing, and the exclusion of relevant facts can render it incomplete and likely to mislead.
Report writing should not incur unnecessary expenses. Cost-effective methods should be used to maintain a consistent level of quality when communicating the content.
Reports can be valuable and practical when they reach the readers promptly. Any delay in the submission of reports renders the preparation of reports futile and sometimes obsolete.
The points mentioned in a report should be arranged in a step-by-step logical sequence and not haphazardly. Distinctive points should have self-explanatory headings and sub-headings. The scientific accuracy of facts is very essential for a report.
Planning is necessary before a report is prepared, as reports invariably lead to decision-making, and inaccurate facts may result in unsuccessful decisions.
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A research report serves as a means of communicating research findings to the readers effectively.
A well-defined research report must define the what, why, who, whom, when, where, and how of the research study. It must help the readers to understand the focus of the information presented.
The report should strike a balance, being sufficiently brief and appropriately extended. It should cover the subject matter adequately while maintaining the reader’s interest.
The report should be written in an objective style, employing simple language. Correctness, precision, and clarity should be prioritized, avoiding wordiness, indirection, and pompous language.
An excellent report integrates clear thinking, logical organization, and sound interpretation of the research findings.
It should not be dull; instead, it should captivate and sustain the reader’s interest.
Accuracy is paramount. The report must present facts objectively, eschewing exaggerations and superlatives.
Presentation clarity is achieved through familiar words, unambiguous statements, and explicit definitions of new concepts or terms.
The logical flow of ideas and a coherent sequence of sentences contribute to a smooth continuity of thought.
Even technical reports should be easily understandable. Translate technicalities into reader-friendly language.
Follow best composition practices, ensuring readability through proper paragraphing, short sentences, and the use of illustrations, examples, section headings, charts, graphs, and diagrams.
Draw sound inferences and conclusions from statistical tables without repeating them in verbal form.
Footnote references should be correctly formatted, and the bibliography should be reasonably complete.
The report should be visually appealing, maintaining a neat and clean appearance, whether typed or printed.
The report should be free from all types of mistakes, including language, factual, spelling, and calculation errors.
In striving for these qualities, the researcher enhances the overall quality of the report.
Research reports are of the following types:
Technical reports are reports which contain detailed information about the research problem and its findings. These reports are typically subject to review by individuals interested in research methodology. Such reports include detailed descriptions of used methods for research design such as universe selection , sample preparation, designing questionnaire , identifying potential data sources, etc. These reports provide a complete description of every step, method, and tool used. When crafting technical reports, we assume that users possess knowledge of research methodology, which is why the language used in these reports is technical. Technical reports are valuable in situations where there is a need for statistical analysis of collected data. Researchers also employ it in conducting a series of research studies, where they can repetitively use the methodology.
When authors prepare a report with a particular layout or design for publishing in an academic or scientific journal, it becomes a “manuscript for journal articles”. Journal articles are a concise and complete presentation of a particular research study. While technical reports present a detailed description of all the activities in research, journal articles are known for presenting only a few critical areas or findings of a study. The readers or audience of journal articles include other researchers, management and executives, strategic analysts and the general public, interested in the topic.
In general, a manuscript for a journal article typically ranges from 10 to 30 pages in length. Sometimes there is a page or word limit for preparing the report. Authors primarily submit manuscripts for journal articles online, although they occasionally send paper copies through regular mail.
Students working towards a Master’s, PhD, or another higher degree generally produce a thesis or dissertation, which is a form of research report. Like other normal research reports, the thesis or dissertation usually describes the design, tools or methods and results of the student’s research in detail.
These reports typically include a detailed section called the literature review, which encompasses relevant literature and previous studies on the topic. Firstly, the work or research of the student is analysed by a professional researcher or an expert in that particular research field, and then the thesis is written under the guidance of a professional supervisor. Dissertations and theses usually span approximately 120 to 300 pages in length.
Generally, the university or institution decides the length of the dissertation or thesis. A distinctive feature of a thesis or a dissertation is that it is quite economical, as it requires few printed and bound copies of the report. Sometimes electronic copies are required to be submitted along with the hard copy of the thesis or dissertations. Compact discs (CDs) are used to generate the electronic copy.
Along with the above-mentioned types, there are some other types of research reports, which are as follows:
A popular report is prepared for the use of administrators, executives, or managers. It is simple and attractive in the form of a report. Clear and concise statements are used with less technical or statistical terms. Data representation is kept very simple through minimal use of graphs and charts. It has a different format than that of a technical one by liberally using margins and blank spaces. The style of writing a popular report is journalistic and precise. It is written to facilitate reading rapidly and comprehending quickly.
An interim report is a kind of report which is prepared to show the sponsors, the progress of research work before the final presentation of the report. It is prepared when there is a certain time gap between the data collection and presentation. In this scenario, the completed portion of data analysis along with its findings is described in a particular interim report.
This type of report is related to the interest of the general public. The findings of such a report are helpful for the decision making of general users. The language used for preparing a summary report is comprehensive and simple. The inclusion of numerous graphs and tables enhances the report’s overall clarity and comprehension. The main focus of this report is on the objectives, findings, and implications of the research issue.
The research abstract is a short presentation of the technical report. All the elements of a particular technical report, such as the research problem, objectives, sampling techniques, etc., are described in the research abstract but the description is concise and easy.
Research reports result from meticulous and deliberate work. Consequently, the preparation of the information can be delineated into the following key stages:
1) Logical Understanding and Subject Analysis: This stage involves a comprehensive grasp and analysis of the subject matter.
2) Planning/Designing the Final Outline: In this phase, the final outline of the report is meticulously planned and designed.
3) Write-Up/Preparation of Rough Draft: The report takes shape during this stage through the composition of a rough draft.
4) Polishing/Finalization of the Research Report: The final stage encompasses refining and polishing the report to achieve its ultimate form.
Logical understanding and subject analysis.
This initial stage focuses on the subject’s development, which can be achieved through two approaches:
Logical development relies on mental connections and associations between different aspects facilitated by rational analysis. Typically, this involves progressing from simple to complex elements. In contrast, chronological development follows a sequence of time or events, with instructions or descriptions often adhering to chronological order.
This marks the second stage in report writing. Once the subject matter is comprehended, the subsequent step involves structuring the report, arranging its components, and outlining them. This stage is also referred to as the planning and organization stage. While ideas may flow through the author’s mind, they must create a plan, sketch, or design. These are necessary for achieving a harmonious succession to become more accessible, and the author may be unsure where to commence or conclude. Effective communication of research results hinges not only on language but predominantly on the meticulous planning and organization of the report.
The third stage involves the writing and drafting of the report. This phase is pivotal for the researcher as they translate their research study into written form, articulating what they have accomplished and how they intend to convey it.
The clarity in communication and reporting during this stage is influenced by several factors, including the audience, the technical complexity of the problem, the researcher’s grasp of facts and techniques, their proficiency in the language (communication skills), the completeness of notes and documentation, and the availability of analyzed results.
Depending on these factors, some authors may produce the report with just one or two drafts. In contrast, others, with less command over language and a lack of clarity about the problem and subject matter, may require more time and multiple drafts (first draft, second draft, third draft, fourth draft, etc.).
This marks the last stage, potentially the most challenging phase in all formal writing. Constructing the structure is relatively easy, but refining and adding the finishing touches require considerable time. Consider, for instance, the construction of a house. The work progresses swiftly up to the roofing (structure) stage, but the final touches and completion demand a significant amount of time.
The rough draft, whether it is the second draft or the n th draft, must undergo rewriting and polishing to meet the requirements. The meticulous revision of the rough draft is what distinguishes a mediocre piece of writing from a good one. During the polishing and finalization phase, it is crucial to scrutinize the report for weaknesses in the logical development of the subject and the cohesion of its presentation. Additionally, attention should be given to the mechanics of writing, including language, usage, grammar, spelling, and punctuation.
Good research possesses certain characteristics, which are as follows:
1. Empirical Basis: It implies that any conclusion drawn is grounded in hardcore evidence collected from real-life experiences and observations. This foundation provides external validity to research results.
2. Logical Approach: Good research is logical, guided by the rules of reasoning and analytical processes of induction (general to specific) and deduction (particular to the public). Logical reasoning is integral to making research feasible and meaningful in decision-making.
3. Systematic Nature: Good research is systematic, which adheres to a structured set of rules, following specific steps in a defined sequence. Systematic research encourages creative thinking while avoiding reliance on guesswork and intuition to reach conclusions.
4. Replicability: Scientific research designs, procedures, and results should be replicable. This ensures that anyone apart from the original researcher can assess their validity. Researchers can use or replicate results obtained by others, making the procedures and outcomes of the research both replicable and transmittable.
5. Validity and Verifiability: Good research involves precise observation and accurate description. The researcher selects reliable and valid instruments for data collection, employing statistical measures to portray results accurately. The conclusions drawn are correct and verifiable by both the researcher and others.
6. Theory and Principle Development: It contributes to formulating theories and principles, aiding accurate predictions about the variables under study. By making sound generalizations based on observed samples, researchers extend their findings beyond immediate situations, objects, or groups, formulating generalizations or theories about these factors.
1. What are the key characteristics of research report?
Scope of Business Research
Data Collection
Questionnaire
Difference between questionnaire and schedule
Measurement
Data Processing
Nature of Research
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What this handout is about.
This handout provides a general guide to writing reports about scientific research you’ve performed. In addition to describing the conventional rules about the format and content of a lab report, we’ll also attempt to convey why these rules exist, so you’ll get a clearer, more dependable idea of how to approach this writing situation. Readers of this handout may also find our handout on writing in the sciences useful.
Why do we write research reports.
You did an experiment or study for your science class, and now you have to write it up for your teacher to review. You feel that you understood the background sufficiently, designed and completed the study effectively, obtained useful data, and can use those data to draw conclusions about a scientific process or principle. But how exactly do you write all that? What is your teacher expecting to see?
To take some of the guesswork out of answering these questions, try to think beyond the classroom setting. In fact, you and your teacher are both part of a scientific community, and the people who participate in this community tend to share the same values. As long as you understand and respect these values, your writing will likely meet the expectations of your audience—including your teacher.
So why are you writing this research report? The practical answer is “Because the teacher assigned it,” but that’s classroom thinking. Generally speaking, people investigating some scientific hypothesis have a responsibility to the rest of the scientific world to report their findings, particularly if these findings add to or contradict previous ideas. The people reading such reports have two primary goals:
Your job as a writer, then, is to fulfill these two goals.
Good question. Here is the basic format scientists have designed for research reports:
This format, sometimes called “IMRAD,” may take slightly different shapes depending on the discipline or audience; some ask you to include an abstract or separate section for the hypothesis, or call the Discussion section “Conclusions,” or change the order of the sections (some professional and academic journals require the Methods section to appear last). Overall, however, the IMRAD format was devised to represent a textual version of the scientific method.
The scientific method, you’ll probably recall, involves developing a hypothesis, testing it, and deciding whether your findings support the hypothesis. In essence, the format for a research report in the sciences mirrors the scientific method but fleshes out the process a little. Below, you’ll find a table that shows how each written section fits into the scientific method and what additional information it offers the reader.
states your hypothesis | explains how you derived that hypothesis and how it connects to previous research; gives the purpose of the experiment/study | |
details how you tested your hypothesis | clarifies why you performed your study in that particular way | |
provides raw (i.e., uninterpreted) data collected | (perhaps) expresses the data in table form, as an easy-to-read figure, or as percentages/ratios | |
considers whether the data you obtained support the hypothesis | explores the implications of your finding and judges the potential limitations of your experimental design |
Thinking of your research report as based on the scientific method, but elaborated in the ways described above, may help you to meet your audience’s expectations successfully. We’re going to proceed by explicitly connecting each section of the lab report to the scientific method, then explaining why and how you need to elaborate that section.
Although this handout takes each section in the order in which it should be presented in the final report, you may for practical reasons decide to compose sections in another order. For example, many writers find that composing their Methods and Results before the other sections helps to clarify their idea of the experiment or study as a whole. You might consider using each assignment to practice different approaches to drafting the report, to find the order that works best for you.
The best way to prepare to write the lab report is to make sure that you fully understand everything you need to about the experiment. Obviously, if you don’t quite know what went on during the lab, you’re going to find it difficult to explain the lab satisfactorily to someone else. To make sure you know enough to write the report, complete the following steps:
Once you’ve completed these steps as you perform the experiment, you’ll be in a good position to draft an effective lab report.
How do i write a strong introduction.
For the purposes of this handout, we’ll consider the Introduction to contain four basic elements: the purpose, the scientific literature relevant to the subject, the hypothesis, and the reasons you believed your hypothesis viable. Let’s start by going through each element of the Introduction to clarify what it covers and why it’s important. Then we can formulate a logical organizational strategy for the section.
The inclusion of the purpose (sometimes called the objective) of the experiment often confuses writers. The biggest misconception is that the purpose is the same as the hypothesis. Not quite. We’ll get to hypotheses in a minute, but basically they provide some indication of what you expect the experiment to show. The purpose is broader, and deals more with what you expect to gain through the experiment. In a professional setting, the hypothesis might have something to do with how cells react to a certain kind of genetic manipulation, but the purpose of the experiment is to learn more about potential cancer treatments. Undergraduate reports don’t often have this wide-ranging a goal, but you should still try to maintain the distinction between your hypothesis and your purpose. In a solubility experiment, for example, your hypothesis might talk about the relationship between temperature and the rate of solubility, but the purpose is probably to learn more about some specific scientific principle underlying the process of solubility.
For starters, most people say that you should write out your working hypothesis before you perform the experiment or study. Many beginning science students neglect to do so and find themselves struggling to remember precisely which variables were involved in the process or in what way the researchers felt that they were related. Write your hypothesis down as you develop it—you’ll be glad you did.
As for the form a hypothesis should take, it’s best not to be too fancy or complicated; an inventive style isn’t nearly so important as clarity here. There’s nothing wrong with beginning your hypothesis with the phrase, “It was hypothesized that . . .” Be as specific as you can about the relationship between the different objects of your study. In other words, explain that when term A changes, term B changes in this particular way. Readers of scientific writing are rarely content with the idea that a relationship between two terms exists—they want to know what that relationship entails.
Not a hypothesis:
“It was hypothesized that there is a significant relationship between the temperature of a solvent and the rate at which a solute dissolves.”
Hypothesis:
“It was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases.”
Put more technically, most hypotheses contain both an independent and a dependent variable. The independent variable is what you manipulate to test the reaction; the dependent variable is what changes as a result of your manipulation. In the example above, the independent variable is the temperature of the solvent, and the dependent variable is the rate of solubility. Be sure that your hypothesis includes both variables.
You need to do more than tell your readers what your hypothesis is; you also need to assure them that this hypothesis was reasonable, given the circumstances. In other words, use the Introduction to explain that you didn’t just pluck your hypothesis out of thin air. (If you did pluck it out of thin air, your problems with your report will probably extend beyond using the appropriate format.) If you posit that a particular relationship exists between the independent and the dependent variable, what led you to believe your “guess” might be supported by evidence?
Scientists often refer to this type of justification as “motivating” the hypothesis, in the sense that something propelled them to make that prediction. Often, motivation includes what we already know—or rather, what scientists generally accept as true (see “Background/previous research” below). But you can also motivate your hypothesis by relying on logic or on your own observations. If you’re trying to decide which solutes will dissolve more rapidly in a solvent at increased temperatures, you might remember that some solids are meant to dissolve in hot water (e.g., bouillon cubes) and some are used for a function precisely because they withstand higher temperatures (they make saucepans out of something). Or you can think about whether you’ve noticed sugar dissolving more rapidly in your glass of iced tea or in your cup of coffee. Even such basic, outside-the-lab observations can help you justify your hypothesis as reasonable.
This part of the Introduction demonstrates to the reader your awareness of how you’re building on other scientists’ work. If you think of the scientific community as engaging in a series of conversations about various topics, then you’ll recognize that the relevant background material will alert the reader to which conversation you want to enter.
Generally speaking, authors writing journal articles use the background for slightly different purposes than do students completing assignments. Because readers of academic journals tend to be professionals in the field, authors explain the background in order to permit readers to evaluate the study’s pertinence for their own work. You, on the other hand, write toward a much narrower audience—your peers in the course or your lab instructor—and so you must demonstrate that you understand the context for the (presumably assigned) experiment or study you’ve completed. For example, if your professor has been talking about polarity during lectures, and you’re doing a solubility experiment, you might try to connect the polarity of a solid to its relative solubility in certain solvents. In any event, both professional researchers and undergraduates need to connect the background material overtly to their own work.
Most of the time, writers begin by stating the purpose or objectives of their own work, which establishes for the reader’s benefit the “nature and scope of the problem investigated” (Day 1994). Once you have expressed your purpose, you should then find it easier to move from the general purpose, to relevant material on the subject, to your hypothesis. In abbreviated form, an Introduction section might look like this:
“The purpose of the experiment was to test conventional ideas about solubility in the laboratory [purpose] . . . According to Whitecoat and Labrat (1999), at higher temperatures the molecules of solvents move more quickly . . . We know from the class lecture that molecules moving at higher rates of speed collide with one another more often and thus break down more easily [background material/motivation] . . . Thus, it was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases [hypothesis].”
Again—these are guidelines, not commandments. Some writers and readers prefer different structures for the Introduction. The one above merely illustrates a common approach to organizing material.
As with any piece of writing, your Methods section will succeed only if it fulfills its readers’ expectations, so you need to be clear in your own mind about the purpose of this section. Let’s review the purpose as we described it above: in this section, you want to describe in detail how you tested the hypothesis you developed and also to clarify the rationale for your procedure. In science, it’s not sufficient merely to design and carry out an experiment. Ultimately, others must be able to verify your findings, so your experiment must be reproducible, to the extent that other researchers can follow the same procedure and obtain the same (or similar) results.
Here’s a real-world example of the importance of reproducibility. In 1989, physicists Stanley Pons and Martin Fleischman announced that they had discovered “cold fusion,” a way of producing excess heat and power without the nuclear radiation that accompanies “hot fusion.” Such a discovery could have great ramifications for the industrial production of energy, so these findings created a great deal of interest. When other scientists tried to duplicate the experiment, however, they didn’t achieve the same results, and as a result many wrote off the conclusions as unjustified (or worse, a hoax). To this day, the viability of cold fusion is debated within the scientific community, even though an increasing number of researchers believe it possible. So when you write your Methods section, keep in mind that you need to describe your experiment well enough to allow others to replicate it exactly.
With these goals in mind, let’s consider how to write an effective Methods section in terms of content, structure, and style.
Sometimes the hardest thing about writing this section isn’t what you should talk about, but what you shouldn’t talk about. Writers often want to include the results of their experiment, because they measured and recorded the results during the course of the experiment. But such data should be reserved for the Results section. In the Methods section, you can write that you recorded the results, or how you recorded the results (e.g., in a table), but you shouldn’t write what the results were—not yet. Here, you’re merely stating exactly how you went about testing your hypothesis. As you draft your Methods section, ask yourself the following questions:
Describe the control in the Methods section. Two things are especially important in writing about the control: identify the control as a control, and explain what you’re controlling for. Here is an example:
“As a control for the temperature change, we placed the same amount of solute in the same amount of solvent, and let the solution stand for five minutes without heating it.”
Organization is especially important in the Methods section of a lab report because readers must understand your experimental procedure completely. Many writers are surprised by the difficulty of conveying what they did during the experiment, since after all they’re only reporting an event, but it’s often tricky to present this information in a coherent way. There’s a fairly standard structure you can use to guide you, and following the conventions for style can help clarify your points.
Increasingly, especially in the social sciences, using first person and active voice is acceptable in scientific reports. Most readers find that this style of writing conveys information more clearly and concisely. This rhetorical choice thus brings two scientific values into conflict: objectivity versus clarity. Since the scientific community hasn’t reached a consensus about which style it prefers, you may want to ask your lab instructor.
Here’s a paradox for you. The Results section is often both the shortest (yay!) and most important (uh-oh!) part of your report. Your Materials and Methods section shows how you obtained the results, and your Discussion section explores the significance of the results, so clearly the Results section forms the backbone of the lab report. This section provides the most critical information about your experiment: the data that allow you to discuss how your hypothesis was or wasn’t supported. But it doesn’t provide anything else, which explains why this section is generally shorter than the others.
Before you write this section, look at all the data you collected to figure out what relates significantly to your hypothesis. You’ll want to highlight this material in your Results section. Resist the urge to include every bit of data you collected, since perhaps not all are relevant. Also, don’t try to draw conclusions about the results—save them for the Discussion section. In this section, you’re reporting facts. Nothing your readers can dispute should appear in the Results section.
Most Results sections feature three distinct parts: text, tables, and figures. Let’s consider each part one at a time.
This should be a short paragraph, generally just a few lines, that describes the results you obtained from your experiment. In a relatively simple experiment, one that doesn’t produce a lot of data for you to repeat, the text can represent the entire Results section. Don’t feel that you need to include lots of extraneous detail to compensate for a short (but effective) text; your readers appreciate discrimination more than your ability to recite facts. In a more complex experiment, you may want to use tables and/or figures to help guide your readers toward the most important information you gathered. In that event, you’ll need to refer to each table or figure directly, where appropriate:
“Table 1 lists the rates of solubility for each substance”
“Solubility increased as the temperature of the solution increased (see Figure 1).”
If you do use tables or figures, make sure that you don’t present the same material in both the text and the tables/figures, since in essence you’ll just repeat yourself, probably annoying your readers with the redundancy of your statements.
Feel free to describe trends that emerge as you examine the data. Although identifying trends requires some judgment on your part and so may not feel like factual reporting, no one can deny that these trends do exist, and so they properly belong in the Results section. Example:
“Heating the solution increased the rate of solubility of polar solids by 45% but had no effect on the rate of solubility in solutions containing non-polar solids.”
This point isn’t debatable—you’re just pointing out what the data show.
As in the Materials and Methods section, you want to refer to your data in the past tense, because the events you recorded have already occurred and have finished occurring. In the example above, note the use of “increased” and “had,” rather than “increases” and “has.” (You don’t know from your experiment that heating always increases the solubility of polar solids, but it did that time.)
You shouldn’t put information in the table that also appears in the text. You also shouldn’t use a table to present irrelevant data, just to show you did collect these data during the experiment. Tables are good for some purposes and situations, but not others, so whether and how you’ll use tables depends upon what you need them to accomplish.
Tables are useful ways to show variation in data, but not to present a great deal of unchanging measurements. If you’re dealing with a scientific phenomenon that occurs only within a certain range of temperatures, for example, you don’t need to use a table to show that the phenomenon didn’t occur at any of the other temperatures. How useful is this table?
As you can probably see, no solubility was observed until the trial temperature reached 50°C, a fact that the text part of the Results section could easily convey. The table could then be limited to what happened at 50°C and higher, thus better illustrating the differences in solubility rates when solubility did occur.
As a rule, try not to use a table to describe any experimental event you can cover in one sentence of text. Here’s an example of an unnecessary table from How to Write and Publish a Scientific Paper , by Robert A. Day:
As Day notes, all the information in this table can be summarized in one sentence: “S. griseus, S. coelicolor, S. everycolor, and S. rainbowenski grew under aerobic conditions, whereas S. nocolor and S. greenicus required anaerobic conditions.” Most readers won’t find the table clearer than that one sentence.
When you do have reason to tabulate material, pay attention to the clarity and readability of the format you use. Here are a few tips:
It’s a little tough to see the trends that the author presumably wants to present in this table. Compare this table, in which the data appear vertically:
The second table shows how putting like elements in a vertical column makes for easier reading. In this case, the like elements are the measurements of length and height, over five trials–not, as in the first table, the length and height measurements for each trial.
1058 |
432 |
7 |
Although tables can be useful ways of showing trends in the results you obtained, figures (i.e., illustrations) can do an even better job of emphasizing such trends. Lab report writers often use graphic representations of the data they collected to provide their readers with a literal picture of how the experiment went.
Remember the circumstances under which you don’t need a table: when you don’t have a great deal of data or when the data you have don’t vary a lot. Under the same conditions, you would probably forgo the figure as well, since the figure would be unlikely to provide your readers with an additional perspective. Scientists really don’t like their time wasted, so they tend not to respond favorably to redundancy.
If you’re trying to decide between using a table and creating a figure to present your material, consider the following a rule of thumb. The strength of a table lies in its ability to supply large amounts of exact data, whereas the strength of a figure is its dramatic illustration of important trends within the experiment. If you feel that your readers won’t get the full impact of the results you obtained just by looking at the numbers, then a figure might be appropriate.
Of course, an undergraduate class may expect you to create a figure for your lab experiment, if only to make sure that you can do so effectively. If this is the case, then don’t worry about whether to use figures or not—concentrate instead on how best to accomplish your task.
Figures can include maps, photographs, pen-and-ink drawings, flow charts, bar graphs, and section graphs (“pie charts”). But the most common figure by far, especially for undergraduates, is the line graph, so we’ll focus on that type in this handout.
At the undergraduate level, you can often draw and label your graphs by hand, provided that the result is clear, legible, and drawn to scale. Computer technology has, however, made creating line graphs a lot easier. Most word-processing software has a number of functions for transferring data into graph form; many scientists have found Microsoft Excel, for example, a helpful tool in graphing results. If you plan on pursuing a career in the sciences, it may be well worth your while to learn to use a similar program.
Computers can’t, however, decide for you how your graph really works; you have to know how to design your graph to meet your readers’ expectations. Here are some of these expectations:
The discussion section is probably the least formalized part of the report, in that you can’t really apply the same structure to every type of experiment. In simple terms, here you tell your readers what to make of the Results you obtained. If you have done the Results part well, your readers should already recognize the trends in the data and have a fairly clear idea of whether your hypothesis was supported. Because the Results can seem so self-explanatory, many students find it difficult to know what material to add in this last section.
Basically, the Discussion contains several parts, in no particular order, but roughly moving from specific (i.e., related to your experiment only) to general (how your findings fit in the larger scientific community). In this section, you will, as a rule, need to:
Let’s look at some dos and don’ts for each of these objectives.
This statement is usually a good way to begin the Discussion, since you can’t effectively speak about the larger scientific value of your study until you’ve figured out the particulars of this experiment. You might begin this part of the Discussion by explicitly stating the relationships or correlations your data indicate between the independent and dependent variables. Then you can show more clearly why you believe your hypothesis was or was not supported. For example, if you tested solubility at various temperatures, you could start this section by noting that the rates of solubility increased as the temperature increased. If your initial hypothesis surmised that temperature change would not affect solubility, you would then say something like,
“The hypothesis that temperature change would not affect solubility was not supported by the data.”
Note: Students tend to view labs as practical tests of undeniable scientific truths. As a result, you may want to say that the hypothesis was “proved” or “disproved” or that it was “correct” or “incorrect.” These terms, however, reflect a degree of certainty that you as a scientist aren’t supposed to have. Remember, you’re testing a theory with a procedure that lasts only a few hours and relies on only a few trials, which severely compromises your ability to be sure about the “truth” you see. Words like “supported,” “indicated,” and “suggested” are more acceptable ways to evaluate your hypothesis.
Also, recognize that saying whether the data supported your hypothesis or not involves making a claim to be defended. As such, you need to show the readers that this claim is warranted by the evidence. Make sure that you’re very explicit about the relationship between the evidence and the conclusions you draw from it. This process is difficult for many writers because we don’t often justify conclusions in our regular lives. For example, you might nudge your friend at a party and whisper, “That guy’s drunk,” and once your friend lays eyes on the person in question, she might readily agree. In a scientific paper, by contrast, you would need to defend your claim more thoroughly by pointing to data such as slurred words, unsteady gait, and the lampshade-as-hat. In addition to pointing out these details, you would also need to show how (according to previous studies) these signs are consistent with inebriation, especially if they occur in conjunction with one another. To put it another way, tell your readers exactly how you got from point A (was the hypothesis supported?) to point B (yes/no).
You need to take these exceptions and divergences into account, so that you qualify your conclusions sufficiently. For obvious reasons, your readers will doubt your authority if you (deliberately or inadvertently) overlook a key piece of data that doesn’t square with your perspective on what occurred. In a more philosophical sense, once you’ve ignored evidence that contradicts your claims, you’ve departed from the scientific method. The urge to “tidy up” the experiment is often strong, but if you give in to it you’re no longer performing good science.
Sometimes after you’ve performed a study or experiment, you realize that some part of the methods you used to test your hypothesis was flawed. In that case, it’s OK to suggest that if you had the chance to conduct your test again, you might change the design in this or that specific way in order to avoid such and such a problem. The key to making this approach work, though, is to be very precise about the weakness in your experiment, why and how you think that weakness might have affected your data, and how you would alter your protocol to eliminate—or limit the effects of—that weakness. Often, inexperienced researchers and writers feel the need to account for “wrong” data (remember, there’s no such animal), and so they speculate wildly about what might have screwed things up. These speculations include such factors as the unusually hot temperature in the room, or the possibility that their lab partners read the meters wrong, or the potentially defective equipment. These explanations are what scientists call “cop-outs,” or “lame”; don’t indicate that the experiment had a weakness unless you’re fairly certain that a) it really occurred and b) you can explain reasonably well how that weakness affected your results.
If, for example, your hypothesis dealt with the changes in solubility at different temperatures, then try to figure out what you can rationally say about the process of solubility more generally. If you’re doing an undergraduate lab, chances are that the lab will connect in some way to the material you’ve been covering either in lecture or in your reading, so you might choose to return to these resources as a way to help you think clearly about the process as a whole.
This part of the Discussion section is another place where you need to make sure that you’re not overreaching. Again, nothing you’ve found in one study would remotely allow you to claim that you now “know” something, or that something isn’t “true,” or that your experiment “confirmed” some principle or other. Hesitate before you go out on a limb—it’s dangerous! Use less absolutely conclusive language, including such words as “suggest,” “indicate,” “correspond,” “possibly,” “challenge,” etc.
We’ve been talking about how to show that you belong in a particular community (such as biologists or anthropologists) by writing within conventions that they recognize and accept. Another is to try to identify a conversation going on among members of that community, and use your work to contribute to that conversation. In a larger philosophical sense, scientists can’t fully understand the value of their research unless they have some sense of the context that provoked and nourished it. That is, you have to recognize what’s new about your project (potentially, anyway) and how it benefits the wider body of scientific knowledge. On a more pragmatic level, especially for undergraduates, connecting your lab work to previous research will demonstrate to the TA that you see the big picture. You have an opportunity, in the Discussion section, to distinguish yourself from the students in your class who aren’t thinking beyond the barest facts of the study. Capitalize on this opportunity by putting your own work in context.
If you’re just beginning to work in the natural sciences (as a first-year biology or chemistry student, say), most likely the work you’ll be doing has already been performed and re-performed to a satisfactory degree. Hence, you could probably point to a similar experiment or study and compare/contrast your results and conclusions. More advanced work may deal with an issue that is somewhat less “resolved,” and so previous research may take the form of an ongoing debate, and you can use your own work to weigh in on that debate. If, for example, researchers are hotly disputing the value of herbal remedies for the common cold, and the results of your study suggest that Echinacea diminishes the symptoms but not the actual presence of the cold, then you might want to take some time in the Discussion section to recapitulate the specifics of the dispute as it relates to Echinacea as an herbal remedy. (Consider that you have probably already written in the Introduction about this debate as background research.)
This information is often the best way to end your Discussion (and, for all intents and purposes, the report). In argumentative writing generally, you want to use your closing words to convey the main point of your writing. This main point can be primarily theoretical (“Now that you understand this information, you’re in a better position to understand this larger issue”) or primarily practical (“You can use this information to take such and such an action”). In either case, the concluding statements help the reader to comprehend the significance of your project and your decision to write about it.
Since a lab report is argumentative—after all, you’re investigating a claim, and judging the legitimacy of that claim by generating and collecting evidence—it’s often a good idea to end your report with the same technique for establishing your main point. If you want to go the theoretical route, you might talk about the consequences your study has for the field or phenomenon you’re investigating. To return to the examples regarding solubility, you could end by reflecting on what your work on solubility as a function of temperature tells us (potentially) about solubility in general. (Some folks consider this type of exploration “pure” as opposed to “applied” science, although these labels can be problematic.) If you want to go the practical route, you could end by speculating about the medical, institutional, or commercial implications of your findings—in other words, answer the question, “What can this study help people to do?” In either case, you’re going to make your readers’ experience more satisfying, by helping them see why they spent their time learning what you had to teach them.
We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.
American Psychological Association. 2010. Publication Manual of the American Psychological Association . 6th ed. Washington, DC: American Psychological Association.
Beall, Herbert, and John Trimbur. 2001. A Short Guide to Writing About Chemistry , 2nd ed. New York: Longman.
Blum, Deborah, and Mary Knudson. 1997. A Field Guide for Science Writers: The Official Guide of the National Association of Science Writers . New York: Oxford University Press.
Booth, Wayne C., Gregory G. Colomb, Joseph M. Williams, Joseph Bizup, and William T. FitzGerald. 2016. The Craft of Research , 4th ed. Chicago: University of Chicago Press.
Briscoe, Mary Helen. 1996. Preparing Scientific Illustrations: A Guide to Better Posters, Presentations, and Publications , 2nd ed. New York: Springer-Verlag.
Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.
Davis, Martha. 2012. Scientific Papers and Presentations , 3rd ed. London: Academic Press.
Day, Robert A. 1994. How to Write and Publish a Scientific Paper , 4th ed. Phoenix: Oryx Press.
Porush, David. 1995. A Short Guide to Writing About Science . New York: Longman.
Williams, Joseph, and Joseph Bizup. 2017. Style: Lessons in Clarity and Grace , 12th ed. Boston: Pearson.
You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill
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Understanding research reports, financial analyst research reports, research report impact, conflicts of interest.
James Chen, CMT is an expert trader, investment adviser, and global market strategist.
A research report is a document prepared by an analyst or strategist who is a part of the investment research team in a stock brokerage or investment bank . A research report may focus on a specific stock or industry sector, a currency, commodity or fixed-income instrument, or on a geographic region or country. Research reports generally, but not always, have actionable recommendations such as investment ideas that investors can act upon.
Research reports are produced by a variety of sources, ranging from market research firms to in-house departments at large organizations. When applied to the investment industry, the term usually refers to sell-side research, or investment research produced by brokerage houses.
Such research is disseminated to the institutional and retail clients of the brokerage that produces it. Research produced by the buy-side, which includes pension funds, mutual funds, and portfolio managers , is usually for internal use only and is not distributed to external parties.
Financial analysts may produce research reports for the purpose of supporting a particular recommendation, such as whether to buy or sell a particular security or whether a client should consider a particular financial product. For example, an analyst may create a report in regards to a new offering being proposed by a company. The report could include relevant metrics regarding the company itself, such as the number of years they have been in operation as well as the names of key stakeholders , along with statistics regarding the current state of the market in which the company participates. Information regarding overall profitability and the intended use of the funds can also be included.
Enthusiasts of the Efficient Market Hypothesis (EMH) might insist that the value of professional analysts' research reports is suspect and that investors likely place too much confidence in the conclusions such analysts make. While a definitive conclusion about this topic is difficult to make because comparisons are not exact, some research papers do exist which claim empirical evidence supporting the value of such reports.
One such paper studied the market for India-based investments and analysts who cover them. The paper was published in the March 2014 edition of the International Research Journal of Business and Management. Its authors concluded that analyst recommendations do have an impact and are beneficial to investors at least in short-term decisions.
While some analysts are functionally unaffiliated, others may be directly or indirectly affiliated with the companies for which they produce reports. Unaffiliated analysts traditionally perform independent research to determine an appropriate recommendation and may have a limited concern regarding the outcome.
Affiliated analysts may feel best served by ensuring any research reports portray clients in a favorable light. Additionally, if an analyst is also an investor in the company on which the report is based, he may have a personal incentive to avoid topics that may result in a lowered valuation of the securities in which he has invested.
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Methodology
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.
First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :
Second, decide how you will analyze the data .
Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.
Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.
Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.
For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .
If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .
Qualitative | to broader populations. . | |
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Quantitative | . |
You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.
Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).
If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.
Primary | . | methods. |
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Secondary |
In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .
In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .
To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.
Descriptive | . . | |
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Experimental |
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Research method | Primary or secondary? | Qualitative or quantitative? | When to use |
---|---|---|---|
Primary | Quantitative | To test cause-and-effect relationships. | |
Primary | Quantitative | To understand general characteristics of a population. | |
Interview/focus group | Primary | Qualitative | To gain more in-depth understanding of a topic. |
Observation | Primary | Either | To understand how something occurs in its natural setting. |
Secondary | Either | To situate your research in an existing body of work, or to evaluate trends within a research topic. | |
Either | Either | To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study. |
Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.
Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.
Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:
Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .
Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).
You can use quantitative analysis to interpret data that was collected either:
Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.
Research method | Qualitative or quantitative? | When to use |
---|---|---|
Quantitative | To analyze data collected in a statistically valid manner (e.g. from experiments, surveys, and observations). | |
Meta-analysis | Quantitative | To statistically analyze the results of a large collection of studies. Can only be applied to studies that collected data in a statistically valid manner. |
Qualitative | To analyze data collected from interviews, , or textual sources. To understand general themes in the data and how they are communicated. | |
Either | To analyze large volumes of textual or visual data collected from surveys, literature reviews, or other sources. Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words). |
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
Research bias
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .
A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.
In statistics, sampling allows you to test a hypothesis about the characteristics of a population.
The research methods you use depend on the type of data you need to answer your research question .
Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.
Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).
In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .
In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.
Other students also liked, writing strong research questions | criteria & examples.
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Fakes and forgeries (Things that are not what they seem to be)
Small and medium-sized enterprises (SMEs) represent 99% of all businesses in the EU. The definition of an SME is important for access to finance and EU support programmes targeted specifically at these enterprises.
Small and medium-sized enterprises (SMEs) are defined in the EU recommendation 2003/361 .
The main factors determining whether an enterprise is an SME are
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| or |
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Medium-sized | < 250 | ≤ € 50 m | ≤ € 43 m | ||
Small | < 50 | ≤ € 10 m | ≤ € 10 m | ||
Micro | < 10 | ≤ € 2 m | ≤ € 2 m |
These ceilings apply to the figures for individual firms only. A firm that is part of a larger group may need to include staff headcount/turnover/balance sheet data from that group too.
Further details include
There are 2 broad types of potential benefit for an enterprise if it meets the criteria
The Commission monitors the implementation of the SME definition and reviews it in irregular intervals. Pursuant to the latest evaluation, the Commission concluded that there is no need for a revision.
On 25 October 2021, we informed stakeholders by holding a webinar with presentations on the SME evaluation's results and next steps.
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The 2024 presidential campaign stands out as the first presumptive rematch between major-party candidates since 1956. It’s also the first time an ex-president has run to reclaim the White House in more than a century.
Another uncommon feature is the presence of several high-profile alternative candidates, including Democratic-scion-turned-independent Robert F. Kennedy Jr., independent Cornel West and three-time Green Party nominee Jill Stein.
Kennedy, an environmental lawyer and anti-vaccine activist , is currently polling in the mid-single digits nationally. He appears to draw support both from people who might otherwise back President Joe Biden and former President Donald Trump, complicating both men’s campaign calculations. (Bear in mind that accurately gauging support for third-party candidates can be tricky .)
But U.S. political history tells us that third-party and independent candidates usually finish a lot lower than where they start.
We examined preelection polls in six presidential contests that featured significant third-party or independent candidates, then reviewed those candidates’ actual shares of the popular vote in the general election.
Not only did support for third-party and independent candidates tend to decline over the course of their campaigns, but their vote shares often came in lower than polls suggested they might.
Here’s an election-by-election look at underperformance by third-party and independent candidates.
Given the unusual dynamics of the 2024 presidential election – including the presence of several potentially significant third-party and independent candidates – Pew Research Center examined how such candidates fared in past elections.
We focused on the six elections over the past 60 years in which the major-party share of the nationwide popular vote was less than 98%. In each of those elections, an independent or third-party candidate won at least 2% of the vote.
For each of those candidates, we obtained support-level data via iPoll , an online archive of historical survey data maintained by Cornell University’s Roper Center for Public Opinion Research. For 1980 and subsequent elections, we limited our analysis to surveys of registered voters. No such surveys were available for the 1968 election, so in that case we used surveys of the national adult population.
Over the decades, survey modes shifted from predominantly face-to-face interviews to landline telephone interviews, and then to landline-plus-cellphone interviews. By 2016, online surveys were making their first appearances, but most polls were still conducted via phone. To avoid any distortions caused by such different survey modes , we used only surveys conducted by the same mode within a given year. This meant that we only used face-to-face surveys in 1968, and only phone surveys in all other years we analyzed.
We also looked at the wording of each individual question to make sure each survey was asking essentially the same thing in similar ways. In particular, we wanted to ensure that candidates were referred to by name and identified by party (or as “independent” when appropriate).
Once we had assembled a list of comparable questions, we plotted support for third-party and independent candidates on a timeline. The final point on each chart represents the candidate’s share of the total nationwide popular vote. For 1968 through 2000, we used figures from America Votes , a long-running compilation of election data. For the 2016 election, we compiled official returns from all 50 states and the District of Columbia.
With two exceptions, all support figures in this analysis include those who said they would vote for or leaned toward the candidate in question. The exceptions are John Anderson in 1980 (because no surveys with “leaner” questions met our inclusion criteria) and Ross Perot in 1992, during the interim period in which he wasn’t actively campaigning (because surveys did not typically ask “leaner” questions about him during this period).
Fresh off his first term as Alabama’s segregationist governor, George Wallace – running a “law and order”-themed campaign under the American Independent Party banner – saw his support rise in polls over the spring and summer leading up to the 1968 election. In April, around 10% of adults nationally said they supported or leaned toward Wallace. By September, that had doubled to 20%. Wallace appeared within reach of his goal: dividing the field enough to throw the election to the House of Representatives , where he could try to bargain his electoral votes for “concessions” on desegregation, voting rights and other issues.
That fall, Republican Richard Nixon’s campaign began warning conservatives that voting for Wallace would only help Democrat Hubert Humphrey. Meanwhile, Democratic-aligned unions worked to pull their members – whom Wallace had targeted – back into Humphrey’s fold. Wallace’s running mate, retired Air Force Gen. Curtis LeMay , also made headlines at his introductory press conference after saying he’d consider using nuclear weapons in Vietnam.
Wallace’s support in the polls began to slide, reaching the mid-teens in the weeks before Election Day. He ended up with 13.5% of the popular vote and 46 electoral votes – not enough to keep Nixon from winning the White House.
Rep. John Anderson of Illinois was trailing badly in the Republican presidential primaries when, in April 1980, he dropped out and said he would run as an independent instead. Anderson’s candidacy generated considerable public interest: Around 20% of registered voters said they would support him, and he continued to poll around that level throughout the spring.
But Anderson’s nascent campaign had to spend much time and energy that spring and summer simply getting his name on state ballots. Anderson faded from view during that summer’s Democratic and Republican conventions. Incumbent President Jimmy Carter, the Democrat, refused to share a debate stage with him in the fall – though Republican nominee Ronald Reagan did debate Anderson one-on-one.
By October, Anderson’s support in polls had dwindled to the 9%-10% range. In the end, he won 6.6% of the national popular vote.
Money and visibility weren’t issues for Ross Perot, the billionaire businessman from Texas who mounted a stop-and-go independent campaign against Republican President George H.W. Bush and his Democratic challenger, Arkansas Gov. Bill Clinton.
Perot’s effort, driven initially by volunteers and appearances on Larry King Live , quickly gained momentum. In March, as Perot’s backers began gathering the hundreds of thousands of petition signatures he would need to get on state ballots, Perot was regularly receiving support from 20% or more of registered voters in polls. By May, about a third of registered voters were telling pollsters they’d vote for or were leaning toward Perot. In a few surveys, he led both Bush and Clinton.
Amid sharpening attacks from Republicans and Democrats , though, Perot’s numbers began falling. In mid-July, when his support was below 20% in most polls, Perot abruptly quit the race .
Although Perot was no longer actively campaigning, his name remained on two dozen state ballots, and some never-say-die supporters continued working to gain him ballot access in additional states. Pollsters continued to ask voters about Perot throughout the summer and fall – especially as speculation grew that he might jump back into the race. While Perot’s support declined steadily during this interim period, in late September around 10% of voters still said they preferred him to Bush or Clinton.
Perot reentered the campaign in early October, and within a few weeks his support had climbed back up to around 20%, including leaners. It began to slip again as Election Day neared, falling to around 15%. In the end, Perot won 18.9% of the popular vote – the best showing by a non-major-party candidate since Theodore Roosevelt 80 years earlier .
Perot wouldn’t come close to that in his second campaign. At the start of the year, when it was still unclear whether he would seek the nomination of the Reform Party (which he had founded the year before), his support among registered voters typically was in the mid-teens.
But Perot’s support declined during the campaign, eventually settling at around 5%-7%, including leaners. His poll numbers did pick up a bit in the run-up to Election Day, when he received 8.4% of the popular vote. Among the minor candidates Perot beat out for third place: consumer advocate Ralph Nader, who took 0.7% representing the Green Party.
Nader had a considerably higher profile four years later, when he was again the Green Party’s nominee. Polls taken during that close, contentious campaign regularly found that around 5% of registered voters said they supported or leaned toward Nader.
That was enough to concern Democrats that Nader threatened Vice President Al Gore’s chances of defeating Republican Texas Gov. George W. Bush. (Whether he in fact did so is still hotly debated among political scientists , journalists and other observers .)
In the end, Nader won only 2.7% of the national popular vote. But in several closely divided states – including Florida and New Hampshire, both of which Bush carried – Nader’s share was enough to potentially swing the outcome.
Another third-party candidate in 2000 received a fair amount of public and media attention: Pat Buchanan, the conservative commentator who had captured the nomination of Perot’s Reform Party. Buchanan polled as high as 4% in the spring, but by fall was mostly in the 1%-2% range. He ended up with less than 0.5% of the popular vote, but did well enough in five states to theoretically (or perhaps not so theoretically ) affect the outcome.
Widespread dissatisfaction with Republican Trump and his Democratic opponent, Hillary Clinton, may have caused more voters than usual to look beyond the major parties. Two candidates in particular received considerable attention: former New Mexico Gov. Gary Johnson – the Libertarian Party nominee – and physician and activist Jill Stein of the Green Party. (Both Johnson and Stein had also run in 2012, though with less impact.)
Johnson polled fairly strongly into the fall, with 8%-12% of registered voters routinely saying that they would vote for him or were leaning toward him. But Johnson’s poll numbers began trending downward, and by Election Day his support level was hovering around 5%-6%. Johnson ended up receiving 3.3% of the vote – the 52-year-old Libertarian Party’s best showing in a presidential election to date.
For her part, Stein often received support from 5%-7% of registered voters in polls taken during the spring and summer of 2016. But her support also eroded as the campaign went on, and she eventually received just over 1% of the popular vote – still the party’s best result since Nader in 2000.
Drew DeSilver is a senior writer at Pew Research Center .
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