Assignment 9: Conduct Correlation and Multiple Regression Results Using SPSS In

Assignment 9: Conduct Correlation and Multiple Regression Results Using SPSS
In

Assignment 9: Conduct Correlation and Multiple Regression Results Using SPSS
In this assignment you will conduct a Pearson’s correlation and a multiple regression. The first analysis provides us an estimate of the magnitude and direction of the relationship between two variables measured at the interval or ratio level (Pearson’s correlation ranges from -1 to 1). The second analysis allows us to predict scores on a continuous dependent variable using two or more independent variables (these can be measured at any of the four levels).
You will use the SPSS Dataset.Therapists.sav file, which contains these seven variables:
(a) ID (Each participant’s identification number),
(b) Gender (Gender of participant: 1. Female, 2. Male)
(c) Age (Participant’s age)
(d) Long.Th (How long participant has provided therapy)
(e) Model (Participant’s preferred model of therapy: 1. Bowen Family Systems, 2. Narrative, 3. Solution-Focused, 4. Integrative)
(f) CPS (Discussed in the Week 5 SPSS Assignment)
(g) LSVS (Discussed in the Week 5 SPSS Assignment)
Part 1. Pearson’s Correlation
You will obtain a correlation matrix for the following four variables: Age, Long.Th, CPS, and LSVS.
a. Conduct the correlational analysis (refer to the SPSS example in the Correlational Design: Two Variables section in Chapter 10 -p. 166- in the Schwartz et al. text). Briefly explain why you do not have dependent nor independent variables in a correlational analysis.
b. Report the results of the correlational analysis in APA format (model your language after the example in the Schwartz et al. text).
c. A correlational analysis with four variables results in six unique coefficients. You will note that a correlational table could be folded diagonally along the left to right diagonal axis (all the 1s), with each triangular half being mirror images of each other. Explain why (a) the diagonal contains all 1s, and (b) each triangle is a mirror image of the other.
d. How many of these six correlations were statistically significant? Pick three of them and explain what you understand about the relationship between these specific variables.
Part 2. Multiple Regression
You will conduct a multiple regression using the following four variables: Gender, Long.Th, CPS, and LSVS.
a. Conduct the correlational analysis (refer to the SPSS example in the Prediction with Several Variables: Multiple Linear Regression section in Chapter 10 – p. 184 – in the Schwartz et al. text). Your dependent variable are the CPS scores, while your three independent variables are Gender, Long.Th, and LSVS scores.
A Venn diagram that provides a visual depiction of what you are exploring with this analysis follows:

Caption: A Venn diagram illustrates how the three independent variables in this regression analysis overlap with the dependent variable, CPS. The area represented by where all four variables overlap reflects the amount of variance in CPS scores explained by Gender, Long.Th, and LSVS scores (combined).
b. Report the results of the regression analysis in APA format (model your language after the example in the Schwartz et al. text)
Regression analyses provide a wealth of information about the variables include in the analysis.
c. Identify which variables were significant individual predictors of variance in CPS scores (changes in the value of that variable were associated with changes in CPS scores). How did you know they were significant? Describe any significant relationships in your own words (e.g., “as variable X went up or down, scores on the CPS went up or down”).
d. What percent of variance in CPS scores was explained by the combination of the three independent variables?
e. Write a paragraph identifying what you would share with a layperson with minimal knowledge of statistics what you learned from this analysis?