Data Analysis And Application.
Data Analysis And Application.
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Unit 8 Data Analysis and Application
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 dummycoded multiple regression and an orthogonalcoded regression with the u08a1data.sav file in the Resources. Data Analysis And Application.
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 dummycoded 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 upsidedown U ( O2).
Use the DAA Template located in the resources to write up your assignment. The deadline for submitting your work is 11:59 PM CST on Sunday of Week 8.
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 dummycoded 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 orthogonalcoded 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.
· Begin with a brief statement reviewing the normality assumption; state your codes for the dummycoded regression and the orthogonal regression.
· Next, paste the SPSS output of the Model Summary for the dummycoded regression.
· Report R, R2, and interpret this effect size.
· Next, paste the ANOVA output.
· Report the F test and state your conclusion regarding the null hypothesis.
· Next, paste the Coefficients output.
· Interpret the b coefficients (i.e., what do the b values represent?) For each b coefficient, report the t tests and pvalues, and for D1 and D2, a statement regarding the null hypothesis. Report the squared semipartial correlations for D1 and D2 with an interpretation of effect size.
· Next, paste the SPSS output of the Model Summary for the orthogonalcoded regression.
· Report R, R2, and interpret the effect size.
· Next, paste the ANOVA output.
· Report the F test and state your conclusion regarding the null hypothesis.
· Next, paste the Coefficients output.
· Interpret the b coefficients (i.e., what do the b values represent?) For each b coefficient, report the t tests and pvalues, and for O1 and O2, a statement regarding the null hypothesis. Report the squared semipartial correlations for O1 and O2 with an interpretation of effect size.
Step 5. Write Section 5 of the DAA. Discuss your conclusions of the both the dummycoded multiple regression and the orthogonalcoded 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 dummycoded and orthogonalcoded regression.
Submit your assignment as an attached Word document.
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