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## analyzing data with multiple predictor variables and one continuous scale DV to investigate comparison of means.

Details:
This problem set introduces you to the use of SPSS for analyzing data with multiple predictor variables and one continuous scale DV to investigate comparison of means. You will perform a multiple regression analysis on the data and report your output.
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.
Download the SPSS/PASW data set file “Module 7 SPSS Data File,” and use it for this assignment.
Download the “Module 7 Problem Set” file and use it for this assignment.
Directions:
Perform the following tasks to complete this assignment:
Conduct necessary analyses using SPSS so you can answer the questions listed in the exercise.
Submit your responses to the exercise questions as a Word document.
Submit the SPSS Output files showing the analyses you performed in SPSS to compute the answers for related questions. NOTE: You will need to copy the SPSS file to a Word doc for submission.

NOTE FROM KING: THIS IS ALL THE INFO ON ASSIGNMENT
Optimism and Longevity
A cancer specialist from the Los Angeles County General Hospital (LACGH) rated patient optimism in 20- to 40-year-old male patients with incurable cancer in 1970. In 1990, the researcher examined hospital records to gather the following data:
• Socioeconomic status (1–7 rating of occupation; higher ratings indicate higher levels of SES)
• Age in 1970
• Optimism in 1970 (1–100 rating, higher scores indicate higher levels of optimism)
• Longevity (years lived after the 1970 diagnosis)
Using the SPSS data file for Module 7 (located in Topic Materials), calculate a simultaneous multiple regression with SES, age, and optimism as the independent variables and longevity as the dependent variable.
1. Do the independent variables correlate statistically significantly and practically with the dependent variable?
2. Is collinearity between the independent variables a concern?
3. What is the R and adjusted R-square for all independent variables entered simultaneously?
4. What variable(s) provide a significant unique contribution(s)?
5. Compose a results section for this statistical analysis.

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