Correlation & Multiple Regression Exercise
Correlation & Multiple Regression Exercise
Walk Through ( Data come from the Interpersonal Relationships dataset
Criterion variable is the Liking People Scale (LPS)
Univariate Analysis
Get the frequencies for each variable. In the table below indicate whether each variable is quantitative or binary
Bivariate Analyses
Get the correlations (and p-values) between the criterion and each predictor. Put those values in the table below.
Multivariate Analysis
Perform the multiple regression analysis and fill in the rest of the table below
R = _________ R² = _________ F = _________ df = ____, ______ p = ________
|Predictor |Is variable |r (p) |b (p) |Bivariate/Multivariate Results |
| |quant or binary?| | |Neither r nor b significant |
| | | | |r & b both sig & same sign |
| | | | |r sig but not b |
| | | | |suppressor effect |
|Gender | | | | |
|Number of moves | | | | |
|Hometown population | | | | |
|Greek affiliation | | | | |
|Number of close friends | | | | |
|Trust Scale score | | | | |
a. Does the multiple regression model work? Where did you look to decide? ____________________________
b. How well does the multiple regression model work? ______________________________________________
c. Interpret each of the correlations (use language appropriate to the binary or quant predictor being interpreted)
|Gender | |
|Number of moves | |
|Hometown population | |
|Greek affiliation | |
|Number of close friends | |
|Trust Scale score | |
d. Interpret each of the regression weights:
|Gender | |
|Number of moves | |
|Hometown population | |
|Greek affiliation | |
|Number of close friends | |
|Trust Scale score | |
Your Turn #1 ( Data come from the Interpersonal Relationships dataset
Criterion variable is the Miller Social Intimacy Scale (MSIS)
Univariate Analysis
Get the frequencies for each variable. In the table below indicate whether each variable is quantitative or binary
Bivariate Analyses
Get the correlations (and p-values) between the criterion and each predictor. Put those values in the table below.
Multivariate Analysis
Perform the multiple regression analysis and fill in the rest of the table below
R = _________ R² = _________ F = _________ df = ____, ______ p = ________
|Predictor |Is variable |r (p) |b (p) |Bivariate/Multivariate Results |
| |quant or binary?| | |Neither r nor b significant |
| | | | |r & b both sig & same sign |
| | | | |r sig but not b |
| | | | |suppressor effect |
|Gender | | | | |
|Hometown population | | | | |
|Greek affiliation | | | | |
|Liking People Scale | | | | |
|Length current/last relationship | | | | |
|Interpersonal Trust Scale | | | | |
a. Does the multiple regression model work? Where did you look to decide? ____________________________
b. How well does the multiple regression model work? ______________________________________________
c. Interpret each of the correlations (use language appropriate to the binary or quant predictor being interpreted)
|Gender | |
|Hometown population | |
|Greek affiliation | |
|Liking People Scale | |
|Length current/last relationship | |
|Interpersonal Trust Scale | |
d. Interpret each of the regression weights:
|Gender | |
|Hometown population | |
|Greek affiliation | |
|Liking People Scale | |
|Length current/last relationship | |
|Interpersonal Trust Scale | |
Your Turn #2 ( Data come from the mreglab_clinical dataset
Criterion variable is the depression
Univariate Analysis
Get the frequencies for each variable. In the table below indicate whether each variable is quantitative or binary
Bivariate Analyses
Get the correlations (and p-values) between the criterion and each predictor. Put those values in the table below.
Multivariate Analysis
Perform the multiple regression analysis and fill in the rest of the table below
R = _________ R² = _________ F = _________ df = ____, ______ p = ________
|Predictor |Is variable |r (p) |b (p) |Bivariate/Multivariate Results |
| |quant or binary?| | |Neither r nor b significant |
| | | | |r & b both sig & same sign |
| | | | |r sig but not b |
| | | | |suppressor effect |
|Stress | | | | |
|Socio-economic status | | | | |
|Salary satisfaction | | | | |
|Financial independence | | | | |
|Marital status | | | | |
|Trait anxiety | | | | |
a. Does the multiple regression model work? Where did you look to decide? ____________________________
b. How well does the multiple regression model work? ______________________________________________
c. Interpret each of the correlations (use language appropriate to the binary or quant predictor being interpreted)
|Stress | |
|Socio-economic status | |
|Salary satisfaction | |
|Financial independence | |
|Marital status | |
|Trait anxiety | |
d. Interpret each of the regression weights:
|Stress | |
|Socio-economic status | |
|Salary satisfaction | |
|Financial independence | |
|Marital status | |
|Trait anxiety | |
Your Turn #3 ( Data come from the mreglab_grad dataset
Criterion variable is the graduate GPA
Univariate Analysis
Get the frequencies for each variable. In the table below indicate whether each variable is quantitative or binary
Bivariate Analyses
Get the correlations (and p-values) between the criterion and each predictor. Put those values in the table below.
Multivariate Analysis
Perform the multiple regression analysis and fill in the rest of the table below
R = _________ R² = _________ F = _________ df = ____, ______ p = ________
|Predictor |Is variable |r (p) |b (p) |Bivariate/Multivariate Results |
| |quant or binary?| | |Neither r nor b significant |
| | | | |r & b both sig & same sign |
| | | | |r sig but not b |
| | | | |suppressor effect |
|gender | | | | |
|Program attending | | | | |
|Rating from letters | | | | |
|Repeated a class | | | | |
|Hours/week working | | | | |
|Undergraduate GPA | | | | |
a. Does the multiple regression model work? Where did you look to decide? ____________________________
b. How well does the multiple regression model work? ______________________________________________
c. Interpret each of the correlations (use language appropriate to the binary or quant predictor being interpreted)
|gender | |
|Program attending | |
|Rating from letters | |
|Repeated a class | |
|Hours/week working | |
|Undergraduate GPA | |
d. Interpret each of the regression weights:
|gender | |
|Program attending | |
|Rating from letters | |
|Repeated a class | |
|Hours/week working | |
|Undergraduate GPA | |
Assignment grade out of 20 points ______________
-----------------------
Grading
r & MR Walk-through ______ 5
r & MR Your Turns ______ 15
Total Graded Points ______ - ______ (points lost - why?)
................
................
In order to avoid copyright disputes, this page is only a partial summary.
To fulfill the demand for quickly locating and searching documents.
It is intelligent file search solution for home and business.
Related download
- multiple regression and correlation
- how to interprete the minitab output of a regression analysis
- correlation and regression
- correlation and regression washington state university
- lakey s ap stats home
- chapter 3 handouts statistical analysis of economic relations
- multiple regression analysis
- statistics 231b sas practice lab 1
- worksheet on correlation and regression
- regression analysis simple
Related searches
- correlation and regression pdf
- correlation and regression analysis pdf
- correlation vs regression statistics
- multiple regression and correlation analysis
- correlation and regression statistics
- correlation and regression ppt
- correlation and regression analysis examples
- correlation and regression examples pdf
- correlation and regression studies
- correlation and regression test
- correlation and regression example problems
- correlation and regression project