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The Effective Use of Graphs

David j slutsky , md.

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Address for correspondence David J. Slutsky, MD The Hand and Wrist Institute, 2808 Columbia Street, Torrance, CA 90503, Email: [email protected]

Graphs are a common method to visually illustrate relationships in the data. The purpose of a graph is to present data that are too numerous or complicated to be described adequately in the text and in less space. Do not, however, use graphs for small amounts of data that could be conveyed succinctly in a sentence. Likewise, do not reiterate the data in the text since it defeats the purpose of using a graph. If the data shows pronounced trends or reveals relations between variables, a graph should be used. If the data doesn't show any significant trend in the evidence, a graph is not the figure of choice. 1

Although there are myriad computer programs that can generate a graph, the author must still heed some basic principles. A basic requirement for a graph is that it is clear and readable. This is determined not only by the font size and symbols but by the type of graph itself. It is important to provide a clear and descriptive legend for each graph. Graphs may have several parts, depending on their format: (1) a figure number, (2) a caption (not a title), (3) a headnote, (4) a data field, (5) axes and scales, (6) symbols, (7) legends, and (8) a credit or source line. For most purposes, design a graph so that the vertical axis (ordinate, Y axis) represents the dependent variable and the horizontal axis (abscissa, X axis) represents the independent variable. Hence, time is always on the X axis. 2 Graphs should always have at minimum a caption, axes and scales, symbols, and a data field. Plotting symbols need to be distinct, legible, and provide good contrast between the figure in the foreground and the background. Open and closed circles provide the best contrast and are more effective than the combination of open circles and open squares. 3 Like the title of the paper itself, each legend should concisely convey as much information as possible about what the graph tells the reader, but it should not provide a summary or interpretation of the results or experimental details. Avoid simply restating the axis labels, such as “temperature vs. time.” It is crucial to choose the correct graph type based on the kind of data to be presented. If the independent and dependent variables are numeric, use line diagrams or scattergrams; if only the dependent variable is numeric, use bar graphs; for proportions, use bar graphs or pie charts. These are briefly described below.

A scattergram is used to show the relationship between two variables and whether their values change in a consistent way, such as analyzing the relationship between the concentration levels of two different proteins.

A line graph is similar to the scattergram except that the X values represent a continuous variable, such as time, temperature, or pressure. It plots a series of related values that depict a change in Y as a function of X. Line graphs usually are designed with the dependent variable on the Y-axis and the independent variable on the horizontal X-axis, such as a Kaplan-Meier analyses survival plots of time-to-event outcomes. The proportion of individuals is represented on the Y-axis as a proportion or percentage, remaining free of or experiencing a specific outcome over time.

A bar graph may consist of either horizontal or vertical columns. The greater the length of the bars, the greater the value. They are used to compare a single variable value between several groups, such as the mean protein concentration levels of a cohort of patients and a control group.

The histogram , also called a frequency distributions graph, is a specialized type of bar graph that resembles a column graph, but without any gaps between the columns. It is used to represent data from the measurement of a continuous variable. Individual data points are grouped together in classes to show the frequency of data in each class. The frequency is measured by the area of the column. These can be used to show how a measured category is distributed along a measured variable. These graphs are typically used, for example, to check if a variable follows a normal distribution, such as the distribution of protein levels between different individuals of a population.

A pie chart shows classes or groups of data in proportion to the whole data set. The entire pie represents all the data, while each slice or segment represents a different class or group within the whole. Each slice should show significant variations. The number of categories should be generally limited to between 3 and 10.

A box plot may be either horizontal or vertical. It is used to display a statistical summary of one or more box-and- variables, such as the minimum, lower quartile, median, and maximum. It may also identify the outlier data. The spacing between the different parts of the box indicates the degree of dispersion and whether the data distribution is symmetrical or skewed.

Some common errors include the following: information in the text is duplicated in graphs, or information in graphs is duplicated in tables. The graph does not have proper legends. The wrong type of graph is chosen to represent the data. The graph is not plotted to scale. Data is not labeled, is inconsistent, interrupted, or exaggerated to produce the desired effect. Another common error is to include a line that suggests an unsubstantiated extrapolation between or beyond the data points. Connecting discrete data points with a continuous line, such as a series of average measurements taken from a group of patients, suggests that there are values between the age groups that fall on the lines, when, in fact, the author cannot know this. A better way to display separate values would be a bar chart, in which each column reflects the average value obtained from each age group. 4 If an extremely large range must be covered and cannot be practically shown with a continuous scale, indicate a discontinuity in the scale and the data field with paired diagonal lines (—//—) indicating a missing extent of the range. 2

• 1. Ng K H, Peh W C. Preparing effective illustrations. Part 1: graphs. Singapore Med J. 2009;50(3):245. [ PubMed ] [ Google Scholar ]
• 2. Council of Science Editors' Scientific Style and Format for Authors, Editors, and Publishers 8th ed. Chicago: University of Chicago Press; 2014 [ Google Scholar ]
• 3. Manual of Style: A Guide for Authors and Editors 10th ed. Oxford: Oxford University Press; 2007 [ Google Scholar ]
• 4. Franzblau L E, Chung K C. Graphs, tables, and figures in scientific publications: the good, the bad, and how not to be the latter. J Hand Surg Am. 2012;37(3):591–596. doi: 10.1016/j.jhsa.2011.12.041. [ DOI ] [ PubMed ] [ Google Scholar ]
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How to Use Tables & Graphs in a Research Paper

It might not seem very relevant to the story and outcome of your study, but how you visually present your experimental or statistical results can play an important role during the review and publication process of your article. A presentation that is in line with the overall logical flow of your story helps you guide the reader effectively from your introduction to your conclusion. 

If your results (and the way you organize and present them) don’t follow the story you outlined in the beginning, then you might confuse the reader and they might end up doubting the validity of your research, which can increase the chance of your manuscript being rejected at an early stage. This article illustrates the options you have when organizing and writing your results and will help you make the best choice for presenting your study data in a research paper.

Why does data visualization matter?

Your data and the results of your analysis are the core of your study. Of course, you need to put your findings and what you think your findings mean into words in the text of your article. But you also need to present the same information visually, in the results section of your manuscript, so that the reader can follow and verify that they agree with your observations and conclusions. 

The way you visualize your data can either help the reader to comprehend quickly and identify the patterns you describe and the predictions you make, or it can leave them wondering what you are trying to say or whether your claims are supported by evidence. Different types of data therefore need to be presented in different ways, and whatever way you choose needs to be in line with your story. 

Another thing to keep in mind is that many journals have specific rules or limitations (e.g., how many tables and graphs you are allowed to include, what kind of data needs to go on what kind of graph) and specific instructions on how to generate and format data tables and graphs (e.g., maximum number of subpanels, length and detail level of tables). In the following, we will go into the main points that you need to consider when organizing your data and writing your result section .

Table of Contents:

Types of data , when to use data tables .

• When to Use Data Graphs 

Common Types of Graphs in Research Papers 

Journal guidelines: what to consider before submission.

Depending on the aim of your research and the methods and procedures you use, your data can be quantitative or qualitative. Quantitative data, whether objective (e.g., size measurements) or subjective (e.g., rating one’s own happiness on a scale), is what is usually collected in experimental research. Quantitative data are expressed in numbers and analyzed with the most common statistical methods. Qualitative data, on the other hand, can consist of case studies or historical documents, or it can be collected through surveys and interviews. Qualitative data are expressed in words and needs to be categorized and interpreted to yield meaningful outcomes. 

Quantitative data example: Height differences between two groups of participants Qualitative data example: Subjective feedback on the food quality in the work cafeteria

Depending on what kind of data you have collected and what story you want to tell with it, you have to find the best way of organizing and visualizing your results.

When you want to show the reader in detail how your independent and dependent variables interact, then a table (with data arranged in columns and rows) is your best choice. In a table, readers can look up exact values, compare those values between pairs or groups of related measurements (e.g., growth rates or outcomes of a medical procedure over several years), look at ranges and intervals, and select specific factors to search for patterns. 

Tables are not restrained to a specific type of data or measurement. Since tables really need to be read, they activate the verbal system. This requires focus and some time (depending on how much data you are presenting), but it gives the reader the freedom to explore the data according to their own interest. Depending on your audience, this might be exactly what your readers want. If you explain and discuss all the variables that your table lists in detail in your manuscript text, then you definitely need to give the reader the chance to look at the details for themselves and follow your arguments. If your analysis only consists of simple t-tests to assess differences between two groups, you can report these results in the text (in this case: mean, standard deviation, t-statistic, and p-value), and do not necessarily need to include a table that simply states the same numbers again. If you did extensive analyses but focus on only part of that data (and clearly explain why, so that the reader does not think you forgot to talk about the rest), then a graph that illustrates and emphasizes the specific result or relationship that you consider the main point of your story might be a better choice.

When to Use Data Graphs

Graphs are a visual display of information and show the overall shape of your results rather than the details. If used correctly, a visual representation helps your (or your reader’s) brain to quickly understand large amounts of data and spot patterns, trends, and exceptions or outliers. Graphs also make it easier to illustrate relationships between entire data sets. This is why, when you analyze your results, you usually don’t just look at the numbers and the statistical values of your tests, but also at histograms, box plots, and distribution plots, to quickly get an overview of what is going on in your data.

Line graphs

When you want to illustrate a change over a continuous range or time, a line graph is your best choice. Changes in different groups or samples over the same range or time can be shown by lines of different colors or with different symbols.

Example: Let’s collapse across the different food types and look at the growth of our four fish species over time.

You should use a bar graph when your data is not continuous but divided into categories that are not necessarily connected, such as different samples, methods, or setups. In our example, the different fish types or the different types of food are such non-continuous categories.

Example: Let’s collapse across the food types again and also across time, and only compare the overall weight increase of our four fish types at the end of the feeding period.

Scatter plots

Scatter plots can be used to illustrate the relationship between two variables — but note that both have to be continuous. The following example displays “fish length” as an additional variable–none of the variables in our table above (fish type, fish food, time) are continuous, and they can therefore not be used for this kind of graph. 

As you see, these example graphs all contain less data than the table above, but they lead the reader to exactly the key point of your results or the finding you want to emphasize. If you let your readers search for these observations in a big table full of details that are not necessarily relevant to the claims you want to make, you can create unnecessary confusion. Most journals allow you to provide bigger datasets as supplementary information, and some even require you to upload all your raw data at submission. When you write up your manuscript, however, matching the data presentation to the storyline is more important than throwing everything you have at the reader. 

Don’t forget that every graph needs to have clear x and y axis labels , a title that summarizes what is shown above the figure, and a descriptive legend/caption below. Since your caption needs to stand alone and the reader needs to be able to understand it without looking at the text, you need to explain what you measured/tested and spell out all labels and abbreviations you use in any of your graphs once more in the caption (even if you think the reader “should” remember everything by now, make it easy for them and guide them through your results once more). Have a look at this article if you need help on how to write strong and effective figure legends .

Even if you have thought about the data you have, the story you want to tell, and how to guide the reader most effectively through your results, you need to check whether the journal you plan to submit to has specific guidelines and limitations when it comes to tables and graphs. Some journals allow you to submit any tables and graphs initially (as long as tables are editable (for example in Word format, not an image) and graphs of high enough resolution. 

Some others, however, have very specific instructions even at the submission stage, and almost all journals will ask you to follow their formatting guidelines once your manuscript is accepted. The closer your figures are already to those guidelines, the faster your article can be published. This PLOS One Figure Preparation Checklist is a good example of how extensive these instructions can be – don’t wait until the last minute to realize that you have to completely reorganize your results because your target journal does not accept tables above a certain length or graphs with more than 4 panels per figure. 

Some things you should always pay attention to (and look at already published articles in the same journal if you are unsure or if the author instructions seem confusing) are the following:

• How many tables and graphs are you allowed to include?
• What file formats are you allowed to submit?
• Are there specific rules on resolution/dimension/file size?
• Should your figure files be uploaded separately or placed into the text?
• If figures are uploaded separately, do the files have to be named in a specific way?
• Are there rules on what fonts to use or to avoid and how to label subpanels?
• Are you allowed to use color? If not, make sure your data sets are distinguishable.

If you are dealing with digital image data, then it might also be a good idea to familiarize yourself with the difference between “adjusting” for clarity and visibility and image manipulation, which constitutes scientific misconduct .  And to fully prepare your research paper for publication before submitting it, be sure to receive proofreading services , including journal manuscript editing and research paper editing , from Wordvice’s professional academic editors .

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An Effective Guide to Explain Graphs in Thesis and Research Paper

10 Popular Online Tools for Representing Graphs

When explaining graphs in a thesis and research paper, it is essential to provide a clear and concise interpretation of the data represented in the graph. In this article, iLovePhD presented you with an effective guide to explain graphs in the thesis and research paper.

Effective Guide to Explaining Graphs in Thesis and Research Papers: Tips and Tools

Title and Caption : Begin by providing a clear title for the graph that summarizes its main purpose or finding. Follow it with a descriptive caption that highlights the key elements and trends depicted in the graph. Make sure the caption provides sufficient context and explains any abbreviations or symbols used.

Introduce the graph : In the text preceding the graph, provide a brief introduction to the topic or research question being addressed. Explain why the graph is relevant and how it contributes to answering the research question or supporting the thesis. This helps readers understand the purpose of the graph before delving into its details.

Describe the axes and variables : Clearly identify and label the axes of the graph. Explain what each axis represents and the units of measurement involved. Additionally, define the variables or data points represented on the graph.

Data Points : Draw attention to significant data points or noteworthy features of the graph, such as peaks, troughs, or sudden changes. Describe these points in the context of the research question or thesis statement. Explain any anomalies or unexpected trends observed in the graph.

Highlight trends or patterns : Analyze the graph and identify any significant trends, patterns, or relationships that can be observed. Explain whether the data shows an increase, decrease, fluctuation, or any other notable pattern. Use comparative language (e.g., “higher than,” “lower than,” “increasing,” and “decreasing”) to highlight these patterns and their significance. Use specific data points or numerical values from the graph to support your analysis.

Statistical Analysis : If applicable, provide statistical analysis of the data presented in the graph. Mention the statistical methods used, such as means, standard deviations, or significance tests. This adds rigor to your explanation and reinforces the credibility of your findings.

Provide supporting evidence : Whenever possible, supplement your explanations with additional evidence or information from your research or other sources. This can help to validate the patterns or trends observed in the graph and strengthen your thesis argument.

Interpret the implications : Discuss the implications and significance of the observed trends or patterns. Explain why these findings are important and how they contribute to your overall thesis or research question. Connect the information presented in the graph to the broader context of your study.

Limitations and Uncertainties : Acknowledge any limitations or uncertainties associated with the graph or the data it represents. Discuss potential sources of error, sample size issues, or confounding factors that may have influenced the results. This demonstrates a thoughtful analysis and helps readers understand the scope and reliability of the findings.

Relate to other parts of your thesis : Consider how the graph aligns with other information or analyses presented in your thesis. Highlight any connections between the graph and previous findings, literature reviews, or theoretical frameworks. This will help to create a cohesive narrative and reinforce the validity of your conclusions.

Use clear and concise language : Write your explanations in a clear and concise manner, avoiding jargon or complex language whenever possible. Aim to make your interpretation accessible to readers who may not have a specialized background in your field.

Include captions and references : Make sure to include a caption for each graph that provides a clear title and describes its content. Additionally, provide appropriate citations or references for the graph , following the citation style guidelines specified by your institution or field of study.

The specific approach to explaining graphs may vary depending on your discipline and the nature of your research. It’s crucial to strike a balance between providing enough information to understand the graph and avoiding excessive detail. Keep your explanations concise and focused on the most relevant aspects of the graph.

10 Popular Online Tools for Representing Graphs:

When it comes to representing graphs in a thesis and research paper, there are several online tools available that can assist you in creating professional and visually appealing visualizations. Here are 10 popular online tools for representing graphs:

Plotly : Plotly provides a wide range of interactive and customizable graph types. It allows you to create visually stunning graphs with options for 2D and 3D re presentations , as well as animations.

Tableau Public : Tableau Public is a powerful data visualization tool that allows you to create interactive graphs and dashboards. You can easily connect your data and create professional-looking visualizations.

Microsoft Excel : Excel offers a range of graphing options and is widely used for data analysis and visualization. It provides a user-friendly interface for creating various types of charts, including bar graphs, line graphs, scatter plots, and more.

Google Charts : Google Charts is a free tool that enables you to create a wide variety of charts and graphs. It offers a simple and intuitive interface with options for customization and interactivity.

D3.js : D3.js is a JavaScript library that allows you to create dynamic and interactive data visualizations. It provides extensive flexibility and control over the design and behaviour of your graphs.

Infogram : Infogram is an easy-to-use tool that enables you to create infographics and data visualizations. It offers a range of graph types and templates to choose from, making it suitable for creating eye-catching visuals for your thesis.

Canva : Canva is a versatile design tool that includes graphing capabilities. It offers a wide range of templates and customization options, allowing you to create visually appealing graphs and charts .

Chart.js : Chart.js is a JavaScript library that provides a simple and responsive way to create static and interactive charts. It is lightweight and easy to implement, making it a popular choice for web-based visualizations.

Lucidchart : Lucidchart is a web-based diagramming tool that can be used for creating various types of graphs and flowcharts. It offers a drag-and-drop interface and collaboration features, making it suitable for complex visualizations.

Adobe Illustrator : Adobe Illustrator is professional design software that allows you to create vector-based graphics, including graphs and charts. It provides advanced customization options and is ideal for creating intricate and detailed visualizations.

These tools offer a range of options for creating graphs and visualizations, catering to different skill levels and design requirements. Choose the tool that best suits your needs and familiarity with the software to effectively represent graphs in your thesis.

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Home » Figures in Research Paper – Examples and Guide

Figures in Research Paper – Examples and Guide

Table of Contents

Figures in research papers are essential visual elements that enhance the presentation of data, summarize complex information, and clarify findings. Whether it’s a graph, chart, image, or diagram, figures help readers quickly interpret and understand the results and key points of a study. This article explores the role of figures in research papers, provides examples, and offers a comprehensive guide for creating effective figures.

Figures in Research Paper

Figures in research papers refer to graphical or visual representations of information, data, or concepts. They are designed to complement the text by presenting information in an easily digestible and visually appealing format. Common types of figures include charts, graphs, photographs, illustrations, and flowcharts.

Examples of Figures in Research Paper

Examples of Figures in Research Papers or Thesis are as follows:

Line graphs Example

Bar graphs Example

Pie charts Example

Scatterplots Example

Tables Example

Photographs or images Example

Diagrams or schematics Example

Purpose of Figures in Research Papers

• Simplify Complex Data : Figures condense large datasets into easily interpretable visuals.
• Enhance Clarity : They help explain concepts or processes that are difficult to describe in words.
• Engage Readers : Visual elements capture attention and make the paper more engaging.
• Highlight Key Findings : Figures emphasize critical results or relationships.
• Support the Narrative : They provide evidence to back up claims made in the text.

Key Components of Figures

To ensure clarity and usability, figures must include the following elements:

• Example : “Figure 1: Annual Growth Rate of Renewable Energy Adoption (2015–2020).”
• Example : “X-Axis: Time (years), Y-Axis: Revenue (in millions).”
• Example : Red bars for 2020 data, blue bars for 2021 data.
• Example : “Source: World Bank Data 2022.”
• Caption : A brief description providing context or additional information about the figure.
• Example : “Figure 2.”

Guide to Using Figures in Research Papers

Step 1: determine the need for figures.

Evaluate whether a figure will improve the clarity or impact of your paper. Use figures to:

• Summarize key data or findings.
• Show relationships between variables.
• Explain processes or workflows.

Step 2: Choose the Right Type of Figure

Select a figure type that best conveys your data or concept:

• Line Graph : Trends over time.
• Bar Graph : Comparisons between groups.
• Scatter Plot : Relationships or correlations between variables.
• Flowchart : Step-by-step processes or decision trees.

Step 3: Design Figures for Clarity

Follow best practices for figure design:

• Use simple and clean visuals.
• Avoid clutter by limiting data points and excessive text.
• Use consistent fonts, colors, and styles across figures.

Step 4: Integrate Figures with the Text

Mention each figure in the main text and explain its relevance. Avoid simply restating what the figure shows; instead, interpret and analyze the data.

• Example in Text : “As shown in Figure 3, the adoption rate of renewable energy increased significantly between 2015 and 2020, particularly in developed countries.”

Step 5: Adhere to Formatting Guidelines

Follow the specific formatting requirements of your journal or citation style (e.g., APA, MLA, or Chicago). Common guidelines include:

• Position figures close to the relevant text.
• Include captions and numbering.
• Ensure high-quality resolution for digital figures.

Step 6: Cite Data Sources

If the figure uses data from external sources, provide proper attribution in the caption or reference list.

Step 7: Use Tools for Figure Creation

Leverage tools to create professional and accurate figures:

• Microsoft Excel : For graphs and charts.
• Tableau : For interactive and advanced data visualizations.
• R and Python : For customized plots and statistical visualizations.
• Canva : For flowcharts and infographics.

Common Mistakes to Avoid

• Overloading Figures : Too much data or detail can confuse readers. Simplify wherever possible.
• Inconsistent Design : Use uniform styles for fonts, colors, and labels across figures.
• Missing Context : Ensure captions provide enough information for standalone understanding.
• Poor Quality : Low-resolution images or graphs can reduce the paper’s credibility.
• Ignoring Guidelines : Failing to follow journal or style-specific formatting rules.

Figures are an invaluable component of research papers, transforming data into visually engaging formats that enhance comprehension and impact. By choosing the appropriate type of figure, following best practices for design, and adhering to formatting standards, researchers can effectively communicate their findings. Whether presenting trends, relationships, or processes, figures make research more accessible and impactful.

• American Psychological Association (2020). Publication Manual of the American Psychological Association (7th ed.). APA.
• Tufte, E. R. (2001). The Visual Display of Quantitative Information . Graphics Press.
• Knaflic, C. N. (2015). Storytelling with Data: A Data Visualization Guide for Business Professionals . Wiley.
• Cleveland, W. S. (1994). The Elements of Graphing Data . Hobart Press.
• Microsoft (2024). “Using Excel for Data Visualization.” Microsoft Corporation.

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Maximizing the Impact of Your Research Paper with Graphs and Charts

The value of visual aids in today’s data-driven study environment cannot be overlooked.

Graphs and charts are effective communication tools that enable academics to convey difficult information to their audience. These visual tools, which range from pie charts to bar graphs, can significantly improve the readability and impact of research articles.

Graphs and charts are indispensable in contemporary research, whether they are used to compare data points, depict trends and patterns, or just break up text-heavy parts.

In this article, the significance of graphs and charts in research papers will be examined, along with their benefits, types of visual aids that are frequently employed, recommended practices for their use, and typical pitfalls to avoid.

By the end of this article, you will have a comprehensive understanding of the role of graphs and charts in research, and how to use them effectively in your next paper.

If you are not well versed with charts and graphs there is a quick fix. Join online c ourses on Data visualization . This will help you learn tricks involved in representing the data in a quick way. If you are still not comfortable the hire a research consultant who will help you in representing the data in a most adorable way. I have written an article on Why Hiring a Research Consultant Can Benefit Your PhD Work? . Please refer the article for further details.

Why add Graphs and Charts to my research paper?

How graphs and charts in research papers are critical, enhance visual appeal and readability of data, convey complex information effectively, enable easy comparison of data points, facilitate understanding of trends and patterns, improved data visualization, enhanced readability, better communication of results, increased credibility, better understanding of data, choosing the right type of graph or chart, making sure the graph or chart is accurate, using clear and concise labelling, adding a title and caption, formatting the graph or chart appropriately, line graphs, scatter plots, best software options for drawing charts and graphs, how do i choose the appropriate scale for my charts and graphs, how do i handle missing data when creating charts and graphs, how to handle huge data sets using charts and graphs, when should i use logarithmic scales in my charts and graphs, how do i ensure that my charts and graphs are accessible to all audiences, including those with disabilities, whether charts and graphs come under copyright protection, what are some common mistakes to avoid when using charts and graphs in research papers, how many graphs and charts should be there in a research paper, what should be the size of graphs and charts in a research paper, can i place charts and graphs at the end of paper instead of in between text, can i place charts and graphs at the end of text as single column instead of two column text, introduction.

Graphs and charts are often used in the Results section of a research paper to visually represent data and findings obtained from experiments or analyses. They may also be included in the Discussion section to support or refute the hypotheses or research questions presented in the Introduction section.

In the Results section, graphs and charts may be used to display statistical analyses such as histograms, scatter plots, and box plots. They can also be used to show trends over time or across different groups, such as line graphs or bar charts. Tables may also be used to present numerical data in a more organized and concise manner.

I have written an article on How to write Results Section of your Research Paper . The article helps you to represent the results in a better fashion, which will in turn increase the chances of paper acceptance.

In the Discussion section, graphs and charts may be used to support the interpretation of the results and to draw conclusions. They may also be used to compare the findings of the current study to previous research or to provide visual examples of the phenomena being studied.

I have written an article on 07 Easy Steps for Writing Discussion Section of a Research Paper . This article will help you in analyzing the charts and graphs to gain better insights.

It is important to note that while graphs and charts can be useful tools in a research paper, they should be used sparingly and only when they add value to the presentation of the data. Too many or poorly designed graphs can make the paper difficult to read and understand.

In research papers, graphs and charts are used to aid in the audience’s comprehension of the material being given. Graphs and charts give the data a visual representation that is simple to comprehend, evaluate, and compare.

Researchers may successfully communicate difficult information using graphs and charts, which increases the impact and accessibility of their findings.

Data from the study are best presented using graphs and charts. They can be used to draw attention to significant patterns and trends in the data, to present information in a comprehensible manner, and to engage viewers.

Graphs and charts can assist you in clearly expressing your ideas and leaving an impact, whether you are summarising data for a research paper or presenting study findings to a big audience.

Advantages of Using Graphs and Charts in Research Papers

The use of graphs and charts in research papers offers many advantages that cannot be achieved through text alone. The following points clearly elaborate on the same.

Long passages of text can be broken up using graphs and charts, which also offer a more understandable visual depiction of the data. Additionally, they can improve the research paper’s aesthetic attractiveness, which will draw readers in and keep them reading.

When given in the form of text or raw statistics, data sets can frequently be convoluted and challenging to comprehend. This information can be made more understandable and easier to interpret for the reader by using graphs and charts. Additionally, they can be used to contrast several data sets, which makes it simpler to spot connections and trends.

Graphs and charts allow researchers to present data in a way that makes it easy to compare different data points. For example, a bar graph can be used to compare the values of different categories, while a line graph can be used to track changes over time.

Data trends and patterns that might not be immediately obvious through text alone might be found using graphs and charts. A histogram, for instance, can be used to see the distribution of data points while a scatter plot can be used to find correlations between two variables. Researchers can more easily make sense of their data by using graphs and charts to better comprehend the underlying patterns and trends.

The Benefits of Using Graphs and Charts in Research Papers

There are many benefits to using graphs and charts in research papers, including:

Graphs and charts can help researchers effectively visualize their data, making it easier for them to see patterns, trends, and relationships within their data. This can help researchers make more informed decisions and draw more accurate conclusions based on their data.

Graphs and charts can make research papers more visually appealing and easier to read. By breaking up long blocks of text, graphs and charts can help to hold the reader’s attention and make the information more engaging.

Graphs and charts can help researchers effectively communicate their results to a variety of audiences. By using visual aids, researchers can effectively convey complex data and ideas in a simple, straightforward manner.

The use of graphs and charts can help to increase the credibility of a research paper. By effectively visualizing their data, researchers can demonstrate that their findings are based on a strong understanding of the data and that their results are robust and reliable.

Graphs and charts can help researchers to better understand their data. By visualizing the data, researchers can identify patterns, relationships, and trends that might not be immediately apparent in raw data or text-based summaries.

By taking advantage of the benefits of using graphs and charts in research papers, researchers can enhance the quality and impact of their research and effectively communicate their findings to a variety of audiences.

Best Practices for Using Graphs and Charts in Research Papers

There are several best practices that researchers should follow when using graphs and charts in their research papers. These include:

It is important to choose the right type of graph or chart to effectively convey the data and results. Researchers should consider the type of data they are working with, the relationships they want to highlight, and the message they want to convey when selecting a graph or chart.

It is important to ensure that the data represented in a graph or chart is accurate and that the graph or chart is properly labelled. Researchers should also be careful to ensure that the scale used in a graph or chart is appropriate for the data being displayed.

Labels should be clear, concise, and accurately describe the data being displayed. Researchers should use labelling to highlight the key points of their data and to make it easy for the reader to understand the message being conveyed.

A title and caption should be included with each graph or chart to provide context and to summarize the key findings. The title should accurately describe the graph or chart, while the caption should provide additional information and context.

The graph or chart should be presented in a clear, uncomplicated, and readable way. In addition to making sure the graph or chart has the right size and placement within the study report, researchers should avoid utilising too many colours or patterns.

Researchers can efficiently utilise graphs and charts to increase the visual appeal and readability of their research papers as well as to properly communicate their data and results by adhering to certain best practises.

Types of Graphs and Charts Commonly used in Research Papers

There are many types of graphs and charts that can be used in research papers, each with their own strengths and uses.

Bar graphs are used to compare the values of different categories or groups. They are best used to display data that is numerical in nature and can be represented in a structured, organized format. Bar graphs can be horizontal or vertical, and can be used to display data in a variety of ways, including grouped bar graphs, stacked bar graphs, and side-by-side bar graphs.

Line graphs are used to track changes over time and to display trends. They consist of a series of points connected by a line and can be used to display data in a variety of ways, including simple line graphs, multiple line graphs, and cumulative line graphs.

Pie charts are used to represent data as a proportion of the whole. They are best used to display data that is categorical in nature and to display the relationships between different categories.

Scatter plots are used to display the relationship between two variables. They consist of a series of points plotted on a set of axes, and can be used to identify correlations between the two variables.

Histograms are used to display the distribution of data. They consist of a series of bars that represent the frequency of data points within a specific range. Histograms are best used to display data that is numerical in nature and to display the distribution of data points over time.

By understanding the different types of graphs and charts, researchers can choose the best visual aid to convey their data and results effectively.

There are several popular software tools for creating graphs and charts for your research paper. These tools are widely used in academia and industry for visualizing data in a visually appealing and professional manner. Here are some of the best software options:

• Microsoft Excel : Excel is a widely used spreadsheet software that comes with a robust charting feature. It allows you to create a wide variety of charts, such as bar charts, line charts, scatter plots, and more. Excel also offers customization options for colors, fonts, and styles to create visually appealing charts.
• MATLAB : MATLAB is a popular software tool used in various fields of research, including engineering, physics, and finance. It has powerful graphing capabilities, with a wide range of plotting functions and customization options. MATLAB also provides advanced data analysis and visualization features, making it suitable for complex research papers.
• R : R is a popular open-source programming language and environment for statistical computing and graphics. It offers extensive libraries for data visualization, such as ggplot2, lattice, and base graphics, which provide a wide range of charting options for creating publication-quality graphs and charts.
• Tableau : Tableau is a powerful data visualization software that provides a user-friendly interface for creating interactive and visually appealing charts and dashboards. It offers a wide range of chart types and customization options, and allows you to connect to various data sources for easy data integration and visualization.
• Adobe Illustrator : Adobe Illustrator is a vector graphics software that provides advanced drawing and design tools for creating high-quality, professional-looking graphs and charts. It offers extensive customization options for colors, fonts, styles, and shapes, allowing you to create visually stunning graphics for your research paper.
• Google Charts : Google Charts is a free web-based tool that allows you to create interactive charts and graphs. It provides a wide range of chart types, such as bar charts, line charts, pie charts, and more, with easy-to-use customization options. Google Charts also offers integration with other Google products, such as Google Sheets, making it convenient for data visualization.

Here’s a comparison of the software tools for drawing graphs and charts:

Note: The cost of these software tools may vary based on different licensing options, usage plans, and academic discounts that may be available.

It’s important to consider factors such as features, customization options, data integration capabilities, interactivity, and cost when choosing the best software for your specific research paper. Depending on your requirements and preferences, you may find one of these software tools more suitable for your needs.

These are some of the best software options for creating graphs and charts for your research paper. Choose the one that best suits your needs and familiarity with the software, and ensure that the resulting graphs and charts are visually appealing and effectively communicate your research findings.

Key factors to consider when choosing the appropriate scale for your charts and graphs, with examples and visual aids:

• Data range: Your chart or graph’s scale should correspond to the range of values in your data. For instance, a bar chart with a scale that only goes up to 1,000 will not accurately depict the full range of the data if the data extends from 0 to 100,000. In this situation, a bigger scale that can hold the entire range of values could be preferable.
• Purpose of the chart or graph: Think about the goal of your graph or chart. Use a smaller scale that zooms in on a specific area of the data if you want to draw attention to a particular trend or pattern. You could wish to zoom in on a certain time period to draw attention to a certain pattern, for instance, if your line chart of temperature trends over time shows trends over time.
• Audience: Consider the audience that your graph or chart is intended to serve. Your data visualisation may need to be more or less explicit and detailed depending on who it is intended for. If you are presenting your study to a general audience, for instance, you might want to use a straightforward bar chart, however, if you are presenting to a more technical audience, you might want to use a more intricate line chart that provides more detail.
• Data distribution: Take your data’s distribution into account. You might want to choose a different scale if your data is skewed or contains outliers in order to better depict the data. For instance, you might wish to use a logarithmic scale if your data are skewed to the right in order to more accurately depict the distribution of the data.

By considering these factors, you can choose an appropriate scale that effectively communicates the data in your chart or graph and enhances the readability and credibility of your research paper.

Handling missing data in charts and graphs can be challenging, but there are several strategies you can use to minimize its impact on the representation of your data:

• Use visual cues: When you have missing data points, you can use visual cues such as dots or a different colour or pattern to indicate the missing information. This helps the reader understand that the data is missing and avoids misleading them with false information.
• Interpolate: In some cases, you may be able to estimate the missing data by interpolating values between two known data points. This can be useful for creating a continuous line chart or graph, but it should be clearly labelled as estimated data.
• Use statistical methods: Statistical methods, such as imputation, can be used to fill in missing data based on patterns in the existing data. This should be done carefully and with caution, as it can introduce bias into the data if not done correctly.
• Leave it out: If the amount of missing data is significant, it may be best to simply exclude it from your charts and graphs. This will avoid giving false impressions of trends or patterns in the data.
• Provide a separate graph or chart: If the missing data is important, you can provide a separate chart or graph that specifically shows the missing data. This allows the reader to see the complete picture, and understand the limitations of the data you are presenting.

When handling missing data, it’s important to be transparent about the methods you used and to clearly label any estimated or imputed data. This will help to ensure the accuracy and reliability of your research paper, and to build trust with your readers.

Handling huge data in charts can be a challenge, but there are several strategies that can help make the data more manageable and easier to understand. Here are some tips for handling huge data in charts:

• Use aggregated data: Aggregating data into categories or grouping similar data points can help reduce the amount of data being displayed and make it easier to understand.
• Filter data: Filtering data to only display relevant information can also help reduce the amount of data in a chart.
• Use multiple charts: If the data is too large to be displayed effectively in a single chart, consider using multiple charts to break down the data into smaller, more manageable parts.
• Use dynamic charts: Dynamic charts, such as interactive line charts or bar charts, allow users to select and view specific data points, making it easier to understand large amounts of data.
• Use colour coding: Color coding data points in a chart can help distinguish between different data sets and make it easier to see trends or patterns.
• Use a smaller time scale: If the data is time-based, consider using a smaller time scale, such as days or weeks instead of months or years, to reduce the amount of data in a chart.
• Use data visualizations: Data visualizations, such as heat maps or treemaps, can help represent large amounts of data in a more manageable and easy-to-understand format.
• Use summary statistics: Summary statistics, such as mean, median, or mode, can help simplify the data and make it easier to understand.
• Use simplifying shapes: Using simplifying shapes, such as circles or squares, can help represent large amounts of data in a way that is easy to understand.
• Consider a combination of methods: Using a combination of the methods above can help effectively handle huge data in charts and make it easier for audiences to understand.

By using these strategies, you can effectively handle huge data in charts and ensure that your data is represented in a clear and concise manner.

A logarithmic scale is a type of scale used in charts and graphs to represent a large range of values in a compact and readable manner. Unlike a linear scale, which represents equal increments of a variable with equal distances, a logarithmic scale represents equal increments of the variable as equal percentages.

The logarithmic scale is particularly useful when dealing with data sets that have an extensive range of values. For example, if a data set has values that range from 1 to 1,000,000, a linear scale would require a very long axis to accommodate all of the values, making it difficult to read and understand. On a logarithmic scale, the axis would be compressed, making it easier to see the trends and patterns in the data.

In research papers, the use of a logarithmic scale can be particularly helpful when dealing with data sets that have a skewed distribution, such as data that has a few extremely large values and many smaller values. By using a logarithmic scale, researchers can better represent the distribution of the data and highlight the trends and patterns that may not be apparent on a linear scale.

It’s important to note that when using a logarithmic scale, the values on the axis are logarithms, not actual values. This means that the increments on the axis represent multiplicative factors, not additive factors. When interpreting a chart with a logarithmic scale, it’s important to consider the scale and understand that the values are represented differently than on a linear scale.

In conclusion, the use of a logarithmic scale can be a powerful tool for researchers when dealing with data sets that have a large range of values. By compressing the axis and representing equal increments of the variable as equal percentages, logarithmic scales can help make data easier to understand and highlight important trends and patterns.

Let’s consider the number of confirmed COVID-19 cases in a country for 10 days. Here is a table representing the data:

As you can see, the logarithmic scale makes it easier to see the relative changes in the number of cases, especially as the values get larger. On a logarithmic scale, equal increments of the number of cases represent equal percentages, rather than equal distances. This allows you to see changes that might not be as noticeable on a linear scale.

To calculate the values for the logarithmic scale, you would take the logarithm (base 10) of each value in the data. Here is an example of how to calculate the logarithm of the value for the 5th day (800 cases):

code log10(800) = 2.903

This means that on a logarithmic scale, the value for the 5th day would be represented as 2.903.

To ensure that your charts and graphs are accessible to all audiences, including those with disabilities, consider the following:

• Use clear and simple language: Use plain language and avoid technical terms when labelling your charts and graphs, to make it easier for everyone to understand the data.
• Provide alternative text: Provide alternative text descriptions for images, including charts and graphs, so that screen readers can describe the content to users with visual impairments.
• Use accessible colours: Avoid using colour as the only means of conveying information, and ensure that the colour contrast between the text and background is high enough to be easily readable by people with colour vision deficiencies.
• Use clear and concise labels: Label the axes and data points clearly and concisely, and include units of measurement where appropriate.
• Use accessible file formats: Save charts and graphs in accessible file formats, such as PDF or SVG, which can be easily read by assistive technology.
• Consider touch and keyboard navigation: Make sure that your charts and graphs are usable for people who navigate the web using touch or keyboard controls, by ensuring that all interactive elements can be operated using keyboard commands.
• Test for accessibility: Test your charts and graphs with assistive technology, such as screen readers, to ensure that they are fully accessible to all users.

By following these guidelines, you can ensure that your charts and graphs are accessible to everyone, regardless of their abilities. This will help to increase the reach and impact of your research paper, and promote greater inclusivity in the scientific community.

It is easier for readers to comprehend complex material when it is presented visually through charts and graphs. It’s crucial to think about whether the charts and graphs you create for a research paper are subject to copyright laws and whether you require permission to use them.

Original works of authorship, such as literary, musical, theatrical, and aesthetic works, are protected by copyright law. If they are made by a person or group and have enough creative expression, charts and graphs might be regarded as original works of authorship.

Research articles frequently utilise charts and graphs that are based on publicly accessible data, such as statistics from the government or data from surveys. 

These kinds of information are typically regarded as being in the public domain and can be utilised without a licence.

Charts and graphs produced by an individual or group, however, and containing a considerable amount of original creative work may be protected by copyright legislation. 

In certain situations, you might need to ask the copyright holder for permission before using the graph or chart in your research report.

When using charts and graphs in a research paper, it’s important to consider the source of the data and whether the chart or graph is protected by copyright law. If you are unsure, it’s always best to err on the side of caution and to obtain permission from the copyright owner before using the chart or graph in your research paper.

When using charts and graphs in research papers, it’s important to avoid common mistakes that can undermine the effectiveness of your data visualization. Here are some common mistakes to watch out for:

• Overcomplicating the visualization: Avoid using too many colours, patterns, or elements in your chart or graph, as this can make it difficult for the reader to understand the data. Stick to simple, clean designs that emphasize the data.
• Ignoring the scale: Be careful when choosing the scale for your chart or graph, as the wrong scale can distort the data and give a false impression of the data.
• Improper labelling: Make sure to label the axes of your chart or graph clearly and accurately, and include units of measurement where appropriate.
• Not using appropriate chart or graph types: Choosing the right chart or graph type is important for effectively communicating the data. For example, if you have categorical data, use a bar chart, not a line chart.
• Ignoring the data distribution: Consider the distribution of your data, and adjust the scale and chart type accordingly. For example, if your data is skewed, you may want to use a logarithmic scale to better represent the data.
• Overloading the chart or graph: Avoid putting too much data into a single chart or graph, as this can make it difficult for the reader to understand the data. Instead, break the data down into multiple charts or graphs as needed.
• Using outdated or irrelevant data: Make sure to use the most up-to-date and relevant data in your charts and graphs, as outdated or irrelevant data can undermine the credibility of your research paper.

By avoiding these common mistakes, you can ensure that your charts and graphs effectively communicate the data.

In conclusion, charts and graphs play a crucial role in visualizing and communicating data in research papers. The use of charts and graphs allows researchers to convey information effectively and efficiently, helping the reader to understand complex data easily. Whether it’s a bar graph, scatter plot, heatmap, or histogram, each type of chart has its unique strengths and weaknesses.

Choosing the right type of chart and using it effectively is crucial to getting your message across in a research paper. Additionally, using a logarithmic scale and ensuring accessibility to all audiences can make your charts and graphs more effective and user-friendly. To make the most of charts and graphs in research, it is important to keep in mind the guidelines, best practices, and common mistakes to avoid.

Frequently Asked Questions

The number of graphs and charts in a research paper can vary depending on the nature of the research, the specific requirements of the paper, and the preferences of the author or the guidelines of the target journal or conference. There is no fixed rule or standard for the exact number of graphs and charts in a research paper. However, it is generally recommended to use graphs and charts judiciously, ensuring that they are relevant, clear, and effectively convey the research findings.

The size of graphs and charts in a research paper should be chosen carefully to ensure that they are clear, readable, and effectively convey the information to the readers. Here are some general guidelines for the size of graphs and charts in a research paper: Legibility: The graphs and charts should be large enough to be easily read and interpreted by the readers, even when printed or displayed at a reduced size. The font size of labels, legends, and annotations should be legible, typically ranging from 10-12 points, depending on the font type. Proportionality: The size of the graphs and charts should be proportional to the available space in the paper and the content being presented. Avoid using excessively small graphs or charts that may be difficult to understand or interpret. Clarity: The graphs and charts should be clear and not overly cluttered. Use appropriate line thicknesses, marker sizes, and bar widths that are visually clear and distinguishable. Avoid overcrowding the graphs or charts with too much information, which may make them difficult to read or interpret. Journal/Conference Guidelines: Follow the guidelines of the target journal or conference for the size of graphs and charts. Some journals or conferences may have specific requirements or recommendations for the size of visuals in research papers. Consistency: Ensure that the size of graphs and charts is consistent throughout the paper. Use a consistent style for fonts, colors, and other graphical elements to maintain a cohesive visual appearance. Accessibility: Consider accessibility requirements, such as ensuring that the size of graphs and charts is suitable for readers with visual impairments. Providing alternative text descriptions for visuals can also enhance accessibility.

Yes, it is common practice in research papers to place charts and graphs at the end of the paper as appendices or as separate sections, especially if they are large or numerous. This can help improve the flow and readability of the main text, as readers can refer to the visuals in the appendices or separate sections as needed without interrupting their reading of the main content.

Yes, you can place charts and graphs at the end of a research paper as single-column visuals, even if the main text is formatted in two columns. However, it’s important to ensure that the placement of visuals at the end of the paper does not disrupt the overall organization and readability of your research paper.

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Research Paper Graph: How to Insert Graphs, Tables & Figures

Simple Ways Of Representing Your Data Using Graphs

Graphs are common items in the academic scenario. They are critical in summarizing and displaying data in a way that is easier for the audience to comprehend.

There exist different graphs that researchers use to have varying impacts. These graphs offer an additional explanation of the topic of your research.

If you cannot do this, you can get our essay writers to handle the task. However, read on if you want to know how to do it.

In our guide on how to write a term paper , we gave you various steps to complete a good paper. This piece offers you more insights on how to insert a graph in a research paper.

How to Insert a Graph in a Research Paper

• Open MS Word and choose Insert.
• Label the axis well. For example, you can label the X-axis using the question asked and let the Y-axis have numbers to indicate how many people answered that way.
• Insert all the collected data in every corresponding cell in the Excel window.
• Create the graph and place it into the research paper.
• Select the chart and settle with the style that best represents your research.
• Put captions and citations in the research paper.
• Select the graph and paste it into your Word document.

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Importance of Graphs and Tables in Research Writing

1. Better Understanding

Some situations prompt us to compare the performance of two scenarios.

The traditional approach involves going through bulky data from both scenarios and later analyzing it, which is time-consuming.

Graphs help the audience to understand your research work easily and more quickly than when represented in figures.

2. Accurate Analysis

Graphs and tables are the only tools that enable the audience to understand and analyze trends easily. They summarize a large amount of data in an easy and interpretable form. Moreover, they help one study and interpret patterns.

3. Easy Sharing of Information

Tables and graphs have a greater role in making your research digestible at visualization. They are perfect avenues to make your research more engaging. At a glance, they will convey the message to the reader instantly.

4. Explores Findings

You will gain in-depth knowledge of the new findings by including tables and graphs in your research. You can use them to understand patterns suppose you are handling business-related concepts.

5. Comparing and Contrasting

It is easier to highlight values with many shared variables and characteristics. As such, it becomes easier in studying patterns and consume the information with ease. They help the audience to understand the data in a comparative state.

6. To Prove a Point

It boosts your understanding when you make tabulated results alongside graphical representation. The reader will easily find the conclusion without understanding the calculations.

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Other Alternatives to Graphs in a Research Paper

A table is a useful tool when you want to show the reader how dependent and independent variables interact. Readers use tables to compare values between groups of related measurements. Tables allow the reader to explore data according to their interest.

One can create such tables by using the Excel program to represent the data wonderfully.

The table should have a title column title and table body. Furthermore, a table should have a descriptive title to act as the topic of your table.

Depending on the discipline, the title can be lengthy or short.

Besides, the table should have a column title to simplify it. The right set of column titles allows the reader to grasp the content.

Finally, the table body is the main area where we put numerical or textual data. Construct the table so that the elements can be read from up to down.

Once you create the table in the Excel sheet, copy-paste them on the center page of your research paper.  More importantly, ensure that you reference it well. Avoid text wrapping in this case. Set your table apart from the text.

Infographics

You can make your research finding more engaging by collecting your data and reporting it in infographics. Before you create an infographic, you should observe the following:

 Begin with a good foundation to create effective graphics.

Some infographics rely on data or quantitative research to explain the information.

You can use the data alone when reporting the findings. The included text appears in labels and headings.

Organize the Information

Organize the information into an outline. You can achieve that through word processing depending on your content.

You should have a beginning, middle, and end. The beginning should have an introductory paragraph. The middle should have figures, facts, and content. The end should have a call to action.

Create a Structure

 It is time to create an outline and translate it into a professional-looking design. Alternatively, expand an existing outline or choose a new document.

Design the Infograghics

 Import the Excel sheets and populate your charts with data directly into the infographic maker. You can select the color palettes, fonts, and icons and move them around the page to your preference.

Refine your work with the right color elements and ensure that you have the correct color that is appealing to your audience.

Inserting the Infograghics

Create an outline that follows the structure of your research paper. As noted before, essays or papers can have charts and infographics , which is definitely in line with the outline.

In addition, fill out the outline using the content, data, or information you referenced in the research paper and present the layout that flows data logically.

Figures take varying forms such as frequency histograms, bar graphs, maps, and drawings. If you are using the figures in your research paper, it is always important to focus on the reader. Use the easiest figure that your reader will use to understand effortlessly.

You can use the figure to present your data more effectively and efficiently. For example, if you want your reader to understand spatial relationships more efficiently, use photographs. Typically, figures should have the following sections:

• Figure Captions: Your figures should be numbered and have descriptive titles. The captions should be clear enough for the reader to understand at a glance. Ensure that you place the captions under the figure.
• Image: Select an image that is simple and easy to understand. Consider the resolution, size, and overall attractiveness.
• Extra Information: Number the illustrations from the manuscripts separately. You can include any other information in the figure to help the reader understand.

You can create a figure from the Excel sheet and format it appropriately. Label the vital parts well for better interpretation of the data. After that, you can copy-paste it into your research paper to present your finding in an analyzed form.

A chart is a graph that features cycles cut into varying sectors. Every sector represents a relative size of value for a whole.

We create charts to represent the quantity proportionally. Furthermore, it can represent many classes of data in a single chart.

The main role of a chart is to place large sums of data in a visual format for better understanding.

In addition, they are more visually appealing than other graphs. Not to forget, a chart offers easy calculation of your data accuracy, making it demand little explanation.  As such, different readers can understand it without minimal struggle.

One can create a chart in Excel by doing the following steps:

• Begin by selecting the data that you want to create your chart.
• Choose the insert option and access the recommended charts.
• On the Recommended charts, select your favorite chart and see how it looks.
• Click OK to select it.
• You can format the chart using the given elements in it.

After that, you can copy-paste it into the research paper on an appropriate page for better readers’ interpretation.

When not handling complex essays and academic writing tasks, Josh is busy advising students on how to pass assignments. In spare time, he loves playing football or walking with his dog around the park.

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Ultimate Guide on Creating Comprehensive Graphs for Your Research Paper

If you have two minutes to skim through a research paper, what would you go through? Probably the introduction, the conclusion, and? The graphs? That’s right! Graphs are the best way to visually illustrate your research paper. Research papers usually have massive amounts of data and complicated concepts to explain. And, graphs can be used […]

If you have two minutes to skim through a research paper, what would you go through? Probably the introduction, the conclusion, and? The graphs? That’s right!

Graphs are the best way to visually illustrate your research paper. Research papers usually have massive amounts of data and complicated concepts to explain.

And, graphs can be used to represent these data and concepts in a visual, easy to understand manner. Graphs can effectively help to deliver the message that you want to convey.

Also, adding graphs to your research paper can make it much, much more interesting. Something that might be needed in an otherwise monotonous research paper.

Apart from visually representing your data, graphs can also give a concrete angle to the idea of your hypothesis and research paper.

But, simply adding graphs for the sake of it won’t do. Graphs are meant to make your thesis sound more interesting and explain things better. But, you can easily go wrong with it by adding graphs that do not necessarily complement your research paper.

A good graph can make the world of difference to your research paper. It can make the text of your research paper sound more self-explanatory. If you are a student, then this means you’ll get better grades for your research paper.

So, in this ultimate guide, let’s look at some super-helpful tricks and tips on adding comprehensive graphs to your research paper to make them more interesting and appealing.

Know Your Audience

Knowing your primary audience is important to understand before you decide on the types of graphs that you want to add. 

Not everyone understands graphs the same way. So, ensure that you understand your audience first before proceeding with the addition of graphs to your research paper.

Think about who is going to read your research paper. Is it a scientist, preschool teacher, or your neighbor who works in a finance firm? Different types of graphs would be suitable for people with different levels of understanding.

Based on the capacity of your audience and how they will perceive your research paper, you can decide on the types of graphs that best suit them. Here’s a list to help you out:

If your audience is less experienced, then you should go with graphs that are easier to understand without any extensive knowledge about graphs. Here are some such types of graphs:

• Linear graph
• Multi-set bar graph

If your audience is well versed with the basics of your research paper’s topic and is from your industry, then you can go with more advanced types of graphs. Here are some advanced types of graphs which you can use for a more experienced audience:

• Stacked bar graph
• Stacked area graph
• Spiral plot
• Point and figure chart
• Choropleth map
• Candlestick chart

Imagine if you were to go for a Choropleth map for an inexperienced audience for your research paper. It would be a total disaster! Your message would not be delivered as efficiently. 

Similarly, a simple linear graph might seem amateur in a research paper meant for scientists, when the concept could have been explained with the help of a more advanced graph.

Hence, knowing your audience is very important to understand while you write your research paper and create comprehensive graphs for it.

Keep a Check on the Aesthetics

While creating and adding graphs to your research paper, it is also important to think about its aesthetics too. There is no point in adding a graph if it looks messy and unclear. Right from the colors, the fonts, to the placement of your graphs, everything counts.

The use of the right colors can completely transform your graphs and your research paper. Whereas if you add colors that look off-putting, then your audience might not be able to read and understand your graphs well. They might even put down your research paper right away. 

Colors have the ability to enhance your graphs and improve their readability. For instance, if you use different colors to represent different data points, then your graph will instantly look more readable for your audience.

The contrast of colors is also an essential aspect to consider. You should avoid using dark backgrounds with lighter colored fonts and plots. As this will decrease the readability.

As a general rule, have a lighter background and contrasting colored elements. For example, if you use a white background for your graph, do not plot your graphs with yellow-colored lines as these will not be distinguishable. Instead, use darker colored lines.

Fonts of your graphs are also a very crucial element. If you use fonts that are too large, then your graph might look messy.

While, if you use fonts that are too small, then your graph might not be readable. Readers might have to strain their eyes to understand your graph. Hence, use the right size for the fonts in your graphs.

Also, try not to choose fancy fonts that are not easily understandable. Go with the standard serif fonts. You should also format your fonts properly. For example, use bold and italic fonts wherever highlighting is necessary. Do not bold the entire text. Use it selectively.

Icons can be a great addition to your research paper’s graphs. They can make your research paper self explanatory. You can use icons to label charts or graphs. Or you can also use them to label different elements of your graphs.

While using icons, you should, again, think about the color contrast. Your icons should look clear and distinguishable in the background. For example, use a darker color icon on a lighter colored background.

The fonts inside your icons also matter. Whether you design your own fonts, or you use make my graph tools, you must ensure that the fonts inside icons (if any) are readable without having to strain the eyes.

Make Your Readers Visualize Effectively

The point of adding any graph, chart, or illustration to your research paper is to help your readers easily understand your point.

Reading and understanding research papers cannot be everyone’s cup of tea. Hence, you should make persistent efforts to make it as easy-to-understand as possible.

Your audience will be able to best understand your graphs only when they can visualize them effectively. Visualization is easy to say, but difficult to implement.

You need to ensure that your graphs are designed in a way so that they can be visualized effectively. For this, you need to look at your graph with a fresh set of eyes.

If your graph seems a little too complicated, try to dial it down by breaking down a single graph into multiple smaller graphs. Or, you can also combine two or more smaller graphs to represent everything on a single graph, if that seems like a better representation.

Try to understand how your readers, who do not know entirely about your topic, look at the graphs. Will they be able to visualize and understand the message you are trying to convey?

If not, then recreate better graphs. If your graph looks plain, take the help of online make my graph tools that can aid you to create beautiful, comprehensive graphs at supper affordable rates.

If you nail this part, then your research paper will be a great resource for everyone to refer to. And, your graphs and visual representations will also be widely shared in your industry.

Know What You Want to Convey

The message you want to deliver or the concept you want to explain to your readers with the help of graphs is also important to consider. 

What exactly do you not want to convey? Do you want to add a visual representation of data? Do you want to create scientific infographics that easily explain your research paper’s findings? Do you want to visually explain the differences between the two sets of data?

Based on the message that you want to convey, you can create different types of graphs. Here are a few types of graphs that can help you get started:

Hierarchical

Any concept that forms a hierarchy can be easily represented using hierarchical graphs.

You can create beautiful graphs with hierarchical representations using an easy-to-use online graphic maker tool like MindTheGraph.

A histogram is a graph using which you can represent the frequency distribution of a set of continuous data. You can visualize the shape of the data points and their underlying distribution.

If your research paper consists of data specific to geographical locations, then you can represent that result with the help of geospatial data. Geospatial graphs represent geographical locations through latitudes, longitudes, or the names of geographic locations.

Multidimensional

Multidimensional graphs can be used to represent data that can be better visualized and represented in more than two dimensions. These can be very effective in helping your readers effectively visualize your data and findings.

You can easily create beautiful graphs in multidimensional using online infographic maker tools like Mind the Graph.

Here’s an example of a template that you can use for creating a multidimensional infographic for your research paper.

Temporal graphs can be used to represent data that usually change with time. You can plot different data points with one of the axes of your graph as the time axis.

Pie charts are a circular statistical graph that can be used to represent different proportions of data.

Scatter plots

Scatter plots can be used to explain the relationship between two sets of data in a visual format. In scatter plots, dots are used to represent different numerical values.

Timetable charts

Timetable charts are used to represent scientific data in the form of timelines.

Venn diagrams

Venn diagrams are one of the most commonly used formats for visual presentation. Venn diagrams are used to show all possible logical relations amongst a finite group of things. These can be great for representing the similarities and differences between two or more things.

Stacked area graphs

A stacked area chart or graph is an extension of an area chart. Here, several groups of data are represented in the graph by stacking them, one above the other.

Stream graphs

Stream graphs are another form of stacked area graphs. In a stream graph, instead of stacking the layers, one above the other, layers are positioned around a central axis.

Stacked bar graphs

Stacker bar graphs are similar to stacked graphs, except where the same concept is applied to bar graphs. Different groups of data are represented by stacking them in the same bar graph, one above the other.

Parallel sets

Parallel sets are used to represent the flow and proportions of data. These represent data frequencies instead of individual data points.

Multi-set bar charts

Multi-set bar charts, also known as clustered bar charts, are a type of bar chart. Here, two or more data sets are represented side by side for better understanding and interpretation. All the bar charts use a common axis that may be X-axis or Y-axis.

Ask Others to Share Their Feedback

Lastly, a new set of eyes to review and critique your research paper’s graphs is almost as crucial as the process of designing the graphs.

You would probably love and admire the graphs you have created. But others might have a completely different opinion about it. Hence, it is best to get others’ opinions on this.

The best way to go about it is to pick people who most likely fit your primary audience. For example, if your research paper is meant for readers experienced in your industry, then pick someone with the same kind of industry experience.

Ask them to review your graph, analyze their initial reaction, and gather their feedback. Are they able to understand your graphs? Is your graph readable and easy-to-digest without you having to explain it in depth?

Asking and answering these questions will help you understand the most likely reaction from your primary audience. 

If the reviewer finds it difficult to understand, you should consider simplifying our graphs. You can do this either by using a simpler type of graph or using multiple graphs in place of one.

Whereas, if the reviewer finds the graphs unnecessary or amateur, then you might consider using more advanced graphs or removing them altogether.

We can conclude by saying that graphs can make or break your research paper. People can perceive your research paper in a completely different light if you have added the right graphs to it.

Right from selecting the type of graphs, to the colors and fonts to use, everything must be carefully thought upon before you start creating graphs. 

Take your time and create good comprehensive graphs for your research paper. And, by doing that, you will find that people appreciate your work a lot more than they would otherwise.

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About Fabricio Pamplona

Fabricio Pamplona is the founder of Mind the Graph - a tool used by over 400K users in 60 countries. He has a Ph.D. and solid scientific background in Psychopharmacology and experience as a Guest Researcher at the Max Planck Institute of Psychiatry (Germany) and Researcher in D'Or Institute for Research and Education (IDOR, Brazil). Fabricio holds over 2500 citations in Google Scholar. He has 10 years of experience in small innovative businesses, with relevant experience in product design and innovation management. Connect with him on LinkedIn - Fabricio Pamplona .

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