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Part 11:50 points] When a researcher wishes to include a categorical variable with more than two ievel in a multiple regression prediction model, additional steps

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Part 11:50 points] When a researcher wishes to include a categorical variable with more than two ievel in a multiple regression prediction model, additional steps are needed to ensure that the results are interpretable. These steps include recoding the categorical variable into several separate, dichotomous variables. This recoding is called 'dum my coding". Using the dataset below, predict the Salary of faculties with the Department they belong AND predict their salary with other predictors [Genden Rank, Years since making Rank, Department}. In Excel, use the IF statement to generate the dum my variable columns for Gender, Rank and Department. Categorical Predictor Varla bles Dummy Coding - making many variables out of one Categorical predictor variables cannot be entered directly into a regression model and be meaningfully interpreted, therefore, some other method of dealing with information of this type must be developed. In general, a categorical variable with k levels will be transformed into k-1 variables each with two levels. For example, if a categorical variable had six ievels, then five dichotomous variables could be constructed that would contain the same information as the single categorical variable. Dichotomous variables have the advantage that they can be directly entered in the regression model. The process of creating dichotomous variables from categorical variables is called dummy coding. Depending upon how the dichotomous variables are constructed, additional information can be gleaned from the analysis. In addition, careful construction will result in uncorrelated dichotomous variables. Dummy Coding with three levels When the categorical variable has three levels and is converted to two dichotomous variables. For example, the dataset below, Dept in the example data has three levels, 1=Family Studies, 2=Biology, and 3=Business. This variable could be dummy coded into two variables, one called FamilyS and one called Biology. If Dept = 1, then FamilyS would be coded with a 1 and Biology with a D. If Dept=2, then FamilyS would be coded with a I] and Biology would be coded with a 1. If Dept=3, then both FamilyS and Biology would be coded with a l]. The dummy coding is represented below. Family 1 1 D Studia Biology 2 1 Business 3 I} D

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