Predictive Power in Prism: Mastering Multiple Linear Regression Analysis

Unlock the power of prediction in your research! In this tutorial, Professor Keenan Hartert from Minnesota State University guides you through performing a multiple linear regression analysis in Prism. Using real student performance data (applicable to any field), we'll build a model to predict a key outcome (final class percentage) based on several independent variables (lab, quiz, and exam scores). Learn how to interpret the results, check critical assumptions, and ensure your model is trustworthy and free from confounding factors. What you'll learn in this video: - How to format your data and set up a multiple linear regression model in Prism. - Interpreting Beta coefficients, p-values, and confidence intervals to identify significant predictors. - Understanding the Variance Inflation Factor (VIF) to detect multicollinearity and ensure variable independence. - Analyzing residual plots to check the normality and validity of your model. - Using the Parameter Covariance matrix to explore relationships between your independent variables. - Graphing your results for effective visualization and communication. 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