assumptions

Check Your Residual Plots to Ensure Trustworthy Regression Results!

Use residual plots to check the assumptions of an OLS linear regression model. If you violate the assumptions, you risk producing results that you can’t trust. Residual plots display the residual values on the y-axis and fitted values, or another variable, on the x-axis. After you fit a regression model, it is crucial to check the residual plots. If your plots display unwanted patterns, you can’t trust the regression coefficients and other numeric results.

In this post, I explain the conceptual reasons why residual plots help ensure that your regression model is valid. I’ll also show you what to look for and how to fix the problems. [Read more…] about Check Your Residual Plots to Ensure Trustworthy Regression Results!

Benefits of Welch’s ANOVA Compared to the Classic One-Way ANOVA

By Jim Frost 63 Comments

Welch’s ANOVA is an alternative to the traditional analysis of variance (ANOVA) and it offers some serious benefits. One-way analysis of variance determines whether differences between the means of at least three groups are statistically significant. For decades, introductory statistics classes have taught the classic Fishers one-way ANOVA that uses the F-test. It’s a standard statistical analysis, and you might think it’s pretty much set in stone by now. Surprise, there’s a significant change occurring in the world of one-way analysis of variance! [Read more…] about Benefits of Welch’s ANOVA Compared to the Classic One-Way ANOVA

How to Analyze Likert Scale Data

By Jim Frost 144 Comments

How do you analyze Likert scale data? Likert scales are the most broadly used method for scaling responses in survey studies. Survey questions that ask you to indicate your level of agreement, from strongly agree to strongly disagree, use the Likert scale. The data in the worksheet are five-point Likert scale data for two groups [Read more…] about How to Analyze Likert Scale Data

The Monty Hall Problem: A Statistical Illusion

By Jim Frost

Who would’ve thought that an old TV game show could inspire a statistical problem that has tripped up mathematicians and statisticians with Ph.Ds? The Monty Hall problem has confused people for decades. In the game show, Let’s Make a Deal, Monty Hall asks you to guess which closed door a prize is behind. The answer is so puzzling that people often refuse to accept it! The problem occurs because our statistical assumptions are incorrect.