How can you visualize experiment results for maximum impact?

2 Simplify and clarify your data

The second step to visualize experiment results is to simplify and clarify your data as much as possible. You should avoid cluttering your chart with unnecessary elements, such as grid lines, borders, legends, labels, or colors that do not add value or meaning. You should also use consistent and meaningful scales, axes, and units, and make sure that your data is accurate and reliable. You should also use descriptive and concise titles, captions, and annotations that explain what your chart shows and why it matters. You should also use appropriate formats, such as percentages, decimals, or fractions, to make your data easy to read and understand.

3 Highlight the key messages

The third step to visualize experiment results is to highlight the key messages that you want your audience to take away from your chart. You should use visual cues, such as colors, shapes, sizes, or symbols, to emphasize the most important or interesting data points, trends, or patterns. You should also use contrast, alignment, or grouping to create a clear hierarchy and structure for your chart. You should also use storytelling techniques, such as captions, annotations, or callouts, to provide context, interpretation, or recommendations based on your data. You should also use charts that support your narrative and argument, and avoid misleading or confusing your audience with false or incomplete information.

4 Test and refine your chart

The fourth step to visualize experiment results is to test and refine your chart before you share it with your audience. You should check your chart for errors, inconsistencies, or ambiguities, and make sure that it meets the standards and expectations of your field or industry. You should also get feedback from your peers, colleagues, or stakeholders, and ask them if they can understand your chart, if they find it interesting or useful, and if they have any questions or suggestions. You should also consider how your chart will be displayed and consumed, such as on a screen, a paper, or a presentation, and adjust your chart accordingly.

5 Use tools and resources

The fifth step to visualize experiment results is to use tools and resources that can help you create and improve your charts. There are many software applications, online platforms, and libraries that can help you generate, customize, and export charts for different purposes and audiences. For example, you can use Excel, Tableau, Power BI, or Google Data Studio to create interactive and dynamic charts. You can also use Python, R, or JavaScript to create charts using code. You can also use online resources, such as blogs, books, podcasts, or courses, to learn more about data visualization best practices and standards, and to get inspired by examples and case studies.

6 Have fun and experiment

The sixth and final step to visualize experiment results is to have fun and experiment with different chart types, data sources, and visual elements. Data visualization is not only a science, but also an art, and you can express your creativity and personality through your charts. You can also challenge yourself and your audience by trying new or unconventional ways to visualize your data, such as using maps, infographics, or animations. You can also use data visualization as a way to explore, discover, or learn new things about your data, your topic, or your field. You can also use data visualization as a way to engage, inform, or persuade your audience, and to spark conversations and collaborations.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?