![]() Third, summarizing the data as mean and SE or SD often causes readers to wrongly infer that the data are normally distributed with no outliers. Bar graphs of paired data erroneously suggest that the groups being compared are independent and provide no information about whether changes are consistent across individuals (Panel A in Fig 2). Figures should ideally convey the design of the study. ![]() Second, additional problems arise when bar graphs are used to show paired or nonindependent data ( Fig 2). The full data may suggest different conclusions from the summary statistics ( Fig 1 and Fig 2). First, many different data distributions can lead to the same bar or line graph ( Fig 1 and Fig 2). Bar and line graphs of continuous data are “visual tables” that typically show the mean and standard error (SE) or standard deviation (SD). īar graphs are designed for categorical variables yet they are commonly used to present continuous data in laboratory research, animal studies, and human studies with small sample sizes. Authors generally use figures to present summary statistics, instead of providing detailed information about the distribution of the data or showing the full data. However, studies of the Journal of the American Medical Association and the British Medical Journal provide compelling evidence that fundamental changes in the types of figures that scientists use are needed. Figures are critically important because they often show the data that support key findings. ![]() Data presentation is the foundation of our collective scientific knowledge, as readers’ understanding of a dataset is generally limited to what the authors present in their publications.
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