July 2024

In the model summary of your regression output, you see values of R, R Square, Adjusted R Square, R Square Change and F Change. This post will teach you the right way of interpretating them with good examples.

You can’t trust outliers and their effect maybe be minimal or larger than you think. Their presence can result in a false positive or nagtive result. Let me walk you through the fundamental steps to address this issue using box and whisker plot.

The sole aim of this tutorial is to teach you how to assess common method bias using Harman’s one-factor test for your study especially when the same measurement instrument is used to collect data for both dependent and independent variables.

P-value is also known as probability value and it ranges from 0 to 1. The interpretation of a p-value varies depending on what one is studying. For instance, while a small p-value less than 0.05 provide good evidence against the null hypotheses for ANOVA, t-test, Pearson’s correlation, regression analysis, etc., in some cases such as […]