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?
Which of the following is NOT a goal of transforming data?
Which of the following transformations is good for measurements that cannot be negative and for values that grow by percentage increases?
Which of the following transformations is good for changing direction of relationships?
Which of the following transformations is not a data transformation technique?
Which of the following is NOT a caution for dealing with regression assumptions?
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