Description
RES 866 Module 5 Problem Set And Discussions
RES 866 Module 5 Problem Set
Details:
Some commonly employed statistical analyses include correlation and regression. In this assignment, you will practice correlation and regression techniques from an SPSS data set.
General Requirements:
Use the following information to ensure successful completion of the assignment:
- Review “SPSS Access Instructions” for information on how to access SPSS for this assignment.
- Access the document, “Introduction to Statistical Analysis Using IBM SPSS Statistics, Student Guide” to complete the assignment.
- Download the file “Bank.sav” and open it with SPSS. Use the data to complete the assignment.
- Download the file “Census.sav” and open it with SPSS. Use the data to complete the assignment.
Directions:
Perform the following tasks to complete this assignment:
- Locate the data set “Bank.sav” and open it with SPSS. Follow the steps in section 10.15 Learning Activity as written. Answer questions 1-3 in the activity based on your observations of the SPSS output.Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.
- Locate the data set “Census.sav” and open it with SPSS. Follow the steps in section 11.16 Learning Activity as written. Answer questions 1, 2, 3, and 5 in the activity based on your observations of the SPSS output. Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.
RES 866 Module 5 Discussions
RES 866 Module 5 DQ 1
Assume that you are interested in the relationship between Graduate Record Examinations (GRE) scores (the total of all subtests) and graduate school grade point averages (GPAs) at the end of their graduate programs. Conveniently, you have access to the GRE scores and GPAs of a large number of graduate students who have graduated from the electrical engineering master’s program in an Ivy League university between 2000 and 2013. The Pearson correlation coefficient did not reach significance. What can you conclude from the data analysis? Can the result be generalized to all graduate students in electrical engineering master’s programs across the United States? Why or why not?
RES 866 Module 5 DQ 2
A researcher asks the question “Is there a relationship between GRE total scores and GPAs in the master’s programs in electrical engineering?” The researcher’s null hypothesis states, “There is no correlation between GRE total score and GPA from an electrical engineering master’s program.” The researcher’s alternative hypothesis states, “There is a positive correlation between GRE total scores and GPA from an electrical engineering master’s program.”
Are these valid hypotheses for the research question? Why or why not? What other observations can you make regarding the hypotheses and research question?
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RES 866 Module 5 Problem Set And Discussions
ACCT 553 DeVry, BIAM 500 DeVry, CIS 500 STR, CIS 558 STR, ENG 105 GCU, FIN 390 DeVry, FIN 504 GCU, HCA 545 GCU, HCA 699 GCU, HLT 306 GCU, HLT 362 GCU, HLT 555 GCU, HLT 610 GCU, HLT 665 GCU, HOSP 594 DeVry, HRM 600 DeVry, MAT 144 GCU, MGMT 600, MGT 599 STR, MGT 655 GCU, MKT 373 GCU, PSY 362 GCU, PSY 565 GCU, PSY 575 GCU, PSY 665 GCU, SOC 102 GCU, SOC 320 GCU, SOC 372 GCU, SOC 412 GCU, NSG 6440 SU
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