The lecture Addressing Issues with Regression Assumptions by David Spade, PhD is from the course Statistics Part 1. It contains the following chapters:
If the regression assumptions are not violated, what do we expect to see in a scatterplot of the residuals?
Which of the following is the best way to handle the presence of subsets or multiple groups in our data set?
If a data point has an xvalue that is far away from the average xvalue, it is said to have what?
Which of the following is the best way to handle influential points?
Which of the following is a common transformation to use for making unimodal distributions that are skewed to the left more symmetric?
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