Students learn how to construct a prediction model incrementally using stepwise linear regression. They also learn:
- about data preparation, and converting categorical variables into a set of dummy variables with numerical values of 0 and 1
- the concept of interaction: 2 factors interact if the effect of 1 factor in making a prediction, depends on the value of another factor
- the concept of partial F-tests — to check that each factor in the model contributes significantly to the accuracy of the model, over and above the rest of the factors in the model
- how to interpret the output from the SPSS statistical software.
Students start work on assignment 1. They start out exploring the data visually and using univariate analysis. They wonder what the purpose of univariate analysis is!
