Topic: Statistics with "R" coding - Part II - Data Analysis and Interpretation

The instructions for Part II mirror those for Part I. Please complete the materials required for each assignment. When you have answered each question, upload your answers, your R script file (or the code pasted into a Word document), and any relevant output to Canvas.

1. A survey was developed to analyze the relationships betweenfour measures of Organizational Culture(Innovation=OC_I; People=OC_P; Openness=OC_O; Achievement=OC_A), three measures of person-organization fit (overallfit=OFIT, culturefit=CFIT, valuesfit=VFIT) and a measure of organizational attraction (ATTR). The data developed from these assessments is contained in the file "CultData.csv". Use this file to conduct the following analyses and reporting.

a. These data come from two organizations (Org 1 and 2). Test the hypothesis that the mean ATTR score for the two organizations is the same. Use whatever H0 and H1 you feel is justified, and use whatever test you think will be appropriate. Please be clear about these choices by providing your logic along with the test itself.

b. What is the standardized effect size associated with the test in 1.a. and how would you interpret its magnitude?

c. One group of researchers hypothesizes that the two distinct fit predictors of values fit (VFIT) and culture fit (CFIT) will do a better job of accounting for variance in the measure of attraction (ATTR) than either the culture variables (OC_O, OC_I, OC_P, and OC_A) or a measure of overall fit (OFIT) by itself. Another group of researchers hypothesizes that the same two distinct fit predictors (VFIT and CFIT) will account for additional variance beyond the culture variables and the measure of overall fit. Explain the difference between these two sets of hypotheses, conduct the relevant analyses for both sets, and interpret whether either or both groups of researchers have support for their hypotheses.

d. Yet another group of researchers hypothesize that Organization moderates the relationship between Overall Fit (OFIT) and Attraction (ATTR) such that the relationship between OFIT and ATTR is stronger for organization 1.Conduct the analyses and interpret your results.

2. An extensive study of organizational attraction examines the relationship of a number of antecedent variables to three types of attraction outcomes-whether an individual believes they are attracted to the organization (Attract), whether they intend to apply for a position with the organization (Intent), and whether they apply for a position with organization (Apply). The raw data for this study can be found in the file FIT.csv.

a. Imagine that a group of researchers were interested in predicting each of the attraction outcomes described above (Attract, Intent, Apply) from the remaining variables in the dataset. After examining descriptive information about all of the variables in FIT.csv and the correlation matrix of the variables, what information can you glean about analytical issues that might arise? After this general consideration, focus more specifically on the correlation matrix. What do these correlations suggest to you about potential regression models that incorporate all of the other variables in the matrix to account for variance in each of the three outcome variables? Do not include the other attraction outcomes as predictors in the regression models you consider. Does the correlation matrix suggest any concerns you would have about interpreting particular regression coefficients?

b. Test the hypothesis that the zero order correlation between gender (where females are coded as 1) and intention to apply (Intent) is greater than zero (i.e., H0: rgender.intent = 0). What conclusions and interpretations do you have?

c. Conduct a multiple regression analysis using Intent to Apply (Intent) as the DV. What is the maximum R2 value that you can produce from any combination of five IVs (i.e., not including the other two attraction outcomes)? What are those IVs and what are the standardized regression coefficients for each in the model generating the highest R2? How do these values compare to the zero order correlation for each variable with the DV? How would you interpret the meaning of these standardized regression coefficients? Finally, which of the 5 predictors is most predictive of Intent? How did you arrive at this decision?

Attachment:- Assignment Files.rar