Beyond Basic Heat Maps: Summarizing & Visualizing Data in Prism

Unlock the full potential of heat maps in Prism! In this tutorial, Professor Keenan Hartert from Minnesota State University guides you through creating both standard and advanced summary heat maps to visualize complex datasets at a glance. Learn how to transform raw data—from Likert scales to continuous student performance metrics—into intuitive, color-coded matrices that reveal hidden patterns and relationships. We'll cover how to use Prism's Multiple Variables format to automatically calculate and display summary statistics (like mean, median, and standard deviation) for any subgroup in your data, saving you hours of manual calculation. What you'll learn in this video: - Creating Standard Heat Maps: Plotting raw data (e.g., Likert scale survey results) in the Grouped format. - Advanced Summary Heat Maps: Using the Multiple Variables format to automatically calculate and visualize averages for subgroups (e.g., average exam score for high vs. low attendance). - Customization: Applying color schemes (like Viridis), adding cell borders and values, and formatting labels for clarity. - Dynamic Analysis: Quickly switching between metrics (mean, median, count, standard deviation) to explore different aspects of your data. - Interpreting Results: Understanding what the color gradients and summary values tell you about your dataset. OTHER FREE USEFUL TOOLS FOR RESEARCHERS Explore our educational resources to advance your knowledge of Prism, statistics and data visualization https://www.graphpad.com/resources