Posted: April 11th, 2021
In this assignment, you will learn how to code dummy variables in a regression model. You will use the IBM SPSS Linear Regression procedure to accurately compute a dummy-coded multiple regression and an orthogonal-coded regression with the u08a1data.sav file
Suppose that a researcher conducts a study to see how level of anxiety ( A1 = low, A2 = medium, A3 = high) predicts exam performance ( Y). The performance ( Y) and anxiety ( A) data are already entered into u08a1data.sav. Your task is to correctly enter the dummy codes to run regression. First, for dummy-coded regression, assume that the researcher wants to compare the medium anxiety group to the low and high anxiety groups. Enter the dummy codes for the low anxiety group contrast ( D1) and the high anxiety group contrast ( D2). Next, generate orthogonal codes for a positive linear trend ( O1) and a quadratic (curvilinear) trend for an upside-down U ( O2).
Use the DAA Template located in the resources to write up your assignment.
Step 1. Write Section 1 of the DAA. In Section 1 of the DAA, articulate your predictor variables, the outcome variable, and the scales of measurement for each variable. Specify the sample size of the data set.
Step 2. Write Section 2 of the DAA. Test the normality assumption of multiple regression with a visual interpretation of the Y histogram.
Step 3. Write Section 3 of the DAA. Specify a research question for dummy-coded regression. Articulate a null hypothesis and alternative hypothesis for the overall regression model. Articulate the null hypothesis and alternative hypothesis for each predictor. Next, articulate a research question for the orthogonal-coded regression. Articulate a null hypothesis and alternative hypothesis for the overall regression model. Articulate the null hypothesis and alternative hypothesis for each predictor. Specify the alpha level.
Step 4. Write Section 4 of the DAA.
Step 5. Write Section 5 of the DAA. Discuss your conclusions of the both the dummy-coded multiple regression and the orthogonal-coded multiple regression as they relate to your stated research question and hypotheses for the overall regression model and the individual predictors. Conclude with an analysis of the strengths and limitations of dummy-coded and orthogonal-coded regression.
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