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:

- 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.

**PSY 870: Module 7 Problem Set**

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**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.

- Do the independent variables correlate statistically significantly and practically with the dependent variable?
- Is collinearity between the independent variables a concern?
- What is the
*R *and adjusted *R*-square for all independent variables entered simultaneously?
- What variable(s) provide a significant unique contribution(s)?
- Compose a results section for this statistical analysis.

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