EDR-8202: Statistics II Week 3 Worksheet SPSS Week 3: Correlation and Regression This week, you will complete two exercises related to both correlation and regression. Part 1: Correlation: Download the data set SPSSexam.sav from this week's resources. Review both the Data View and the Variable View to obtain a general understanding of the data. To add a greater detail to the variables in this set, Exam is the score on a SPSS exam (as a percent), Computer is a score on a highly reliable and valid Computer Literacy Inventory, Lecture is the percent of Lecture Attendance, Numeracy is a score on a highly reliable and valid Numeracy Profile, and University is simply two universities. Using SPSS (Analyze > Correlate), conduct the following correlation calculations (conduct all analyses as a two tail test): A Pearson's correlation between Computer (Literacy) and Exam (% on SPSS test). A Partial correlation on the same two variables with Lecture (Attendance) controlled. A Point Bi-serial correlation between Exam (% SPSS test) and University. Re-calculate the correlation between Computer (Literacy) and Exam (% on SPSS test) as a Spearman's rho and a Kendell's tau. Using SPSS, conduct the same correlation calculations as one tail tests. Using scholarly writing and proper APA format, please complete, and then submit the following: 1 The statistical results for each computed correlation above (both two tail and one tail tests). 2 Identify whether each computed correlation was significant or non-significant (both two tail and one tail tests). 3 Briefly interpret the results for each computed correlation above (both two tail and one tail tests). 4 Explain your overall observations about the correlations and the significance levels when you conducted one tail vs. two tail tests. 5 Compare the correlations and significance levels between Computer (Literacy) and Exam (% on SPSS test), when calculated as a Pearson's, Spearman's, or Kendell's. 6 Include an appendix containing all SPSS output (copied and pasted) for the items above. Part 2: Regression: For part 2, address regression in two parts: A and B. Download the data set Lacourse et al. (2001) Females.sav from this week's resources, and use for both parts A and B of the following assignment. Review both the Data View and the Variable View to obtain a general understanding of the data. Part A: Regression 7.5.2017 2017 Northcentral University 10000 E. University Drive, Prescott Valley, Arizona 86314 USA www.ncu.edu p: 928-541-7777 f: 928-541-7817 EDR-8202: Statistics II (continued) In this study, the researcher is interested in predicting Feelings of Social Isolation (outcome variable) using Age, Drug Use, and Father's Negligence as predictor variables. Using the Regression/Linear function, conduct the simple regression analysis for each of the predictor variables of Age, Drug Use, and Father's Negligence, with Feelings of Social Isolation as the outcome variable. Using all of variables, use the Regression/Linear function to conduct the multiple regression analysis of stepwise entry and forced entry (called Enter in the Methods drop down). For the forced entry, perform the statistics of Durbin-Watson and Collinearity. Use scholarly writing and proper APA format to complete the following: 1. Briefly compare the simple regression results. 2. Briefly discuss the gain in understanding from moving from three single regressions to one regression with three predicting variables. 3. Present two tables in APA style. In Table 1, show the multiple regression results for the Forced entry regression model, including the Collinearity statistics. In Table 2, show the regression ANOVA. 4. Discuss each of these two tables, including a discussion of the Durbin-Watson test and of the Collinearity statistic. 5. Include an appendix that contains all SPSS output (copied and pasted) for the items above. Part B: Regression In this study, the researcher is also interested in predicting Suicidal Risk (outcome variable) using Age, Drug Use, and Father's Negligence as predictor variables. Using Regression/Binary Logistic analysis, conduct an analysis with Suicide Risk as the outcome variable and Drug Use as the predictor variable. Using Regression/Binary Logistic analysis, conduct an analysis with Suicide Risk as the outcome variable and Age, Drug Use, and Father's Negligence as the predictor variables. Using Regression/Binary Logistic analysis, conduct an analysis with Suicide Risk as the outcome variable and Isolation, Self-Estrangement, and Mother's Negligence as the predictor variables. Using scholarly writing and proper APA format, please complete, and then submit the following: 1. Briefly explain the added value of moving from one predictor variable (Drug Use) to three predictor variables (Age, Drug Use, and Father's Negligence). 2. Present one table based on the analysis with three predictor variables (Age, Drug Use, and Father's Negligence). In this table, show the resulting prediction model alone with the Wald Statistics and Exp(B). 3. Briefly discuss the results shown in the table. As part of the discussion, include the meaning of Wald and Exp(B). 4. Determine if the second set of predictor variables (Isolation, Self-Estrangement, and Mother's Negligence) was a more effective set, and then explain why or why not. 5. Include an appendix that contains all SPSS output (copied and pasted) for the items above. 7.5.2017 2017 Northcentral University Page 2 of 2