This is an EXCEL LINK of the data:

https://docs.google.com/spreadsheets/d/1a6FiZmx2WWqDSqRV3E5SLORHRMi3fr3vHQTJwg2yrds/edit?usp=sharing

Q6. Researchers are interested to know if it is the enduring dispositional characteristic of 0C that best explains lower sIgA concentration or if it is due to efforts or rewards. Conduct a regression analysis and detail which variable is most associated (even if not significant) with sIgA (:17. In regard to variables used in 0.6, you will have noted that ERIratio was not entered as a predictor. The researcher was concerned that the inclusion of this variable may have violated the assumption of multicollinearitv. Run an analysis to determine if this set of variables (including ERIratio), violate the assumption of m ulticollinearitv when predicting sIgA. Next, explain whv this regression result, with four predictors, is better or worse, in terms of the F test and effect size, than that in C16