the researcher

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. The deadline for submitting your work is 11:59 PM CST on  Sunday of Week 8.

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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.

  • Begin with a brief statement reviewing the normality assumption;  state your codes for the dummy-coded regression and the orthogonal  regression.
  • Next, paste the SPSS output of the Model Summary for the dummy-coded regression.
  • Report RR2, 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 p-values, 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 orthogonal-coded regression.
  • Report RR2, and interpret the effect size.
  • Next, paste the ANOVA output.

 

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the researcher was first posted on March 25, 2020 at 1:55 pm.
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