Soc. 3155 -  Review for Exam 3

 

Multiple Choice: Will cover the following terms and concepts:

  Elaboration of crosstab

Control variable

Partial table

Direct effect

Spurious effect

Intervening variable effect

Interaction effect

Suppressor effect

Correlation

Coefficient of determination (r2)

Symbols for observed and predicted y’s

Intercept

Slope

Residual

Interpretation of slopes and intercept in bivariate and multiple regression

Regression, residual, and total SS in bivariate and multiple regression

Explained and unexplained variation

Residual variance in multiple regression

F-test in bivariate and multiple regression - what does it tell us?

t-test on slope - what does it tell us?

 

Given results from SPSS crosstabs or regression, you should be able to draw conclusions. 

 

Problems:

 Given a crosstab with controls, you should be able to write about the results and draw conclusions.

Given a set of data and some preliminary calculations for bivariate and multiple regression, you should be able to do the following:

Calculate and interpret a correlation

Calculate and interpret the slopes and intercept for bivariate and multiple regression

Write the prediction equation and use it to make a prediction for bivariate and multiple regression

Calculate the three sums of squares for bivariate and multiple regression

Calculate and interpret R2 for bivariate and multiple regression

Complete the ANOVA summary table, give a decision and interpretation for bivariate and multiple regression

 

Practice Problem:

 

Minnesotans love to think about fishing! For some, this raises the issue of whether fishing success is a matter of skill, persistence, or luck. You spend a sunny Saturday at your favorite fishing lake, interviewing a simple random sample of fisherpersons, and recording their number of fish caught (Y), years of fishing experience (X) and hours spent fishing that day (Z). The data, along with some of the preliminary calculations, are presented below:

 

# fish caught (Y)

Years of experience (X)

Hours spent fishing (Z)

6

10

6

0

3

3

5

5

4

3

1

2

0

4

2

8

20

8

4

8

5

 1

10

2

2

8

5

1

1

3

 

mean of Y = 3 fish
mean of X = 7 years
mean of Z = 4 hours

(The values below are all in deviation units)

∑Y2= 66          ∑ X2 =290       ∑Z2= 36

∑XY= 97        ∑ZY=  41        ∑XZ=82

 

1. Calculate the slopes and the intercept for the bivariate regression of number of fish caught (Y) on years of experience (X). Write the prediction equation.

2. Interpret the slope and intercept calculated in part 1.

3. If a person has 7 years of experience, how many fish is s/he predicted to catch?

4. Calculate the regression, residual, and total sums of squares. Calculate and interpret the R2.

5. Test the null hypothesis that years of experience explains no variation in number of fish caught among the population of persons who fish.

6. Calculate the slopes and the intercept for the multiple regression of number of fish caught (Y) on years of experience (X) and hours spent fishing (Z). Write the prediction equation.

7. Interpret both of the slopes calculated in problem 6.

8. If a person with 10 years of experience spends 5 hours fishing, how many fish is s/he predicted to catch?

9. Calculate the regression, residual, and total sums of squares for the multiple regression. Calculate and interpret the R2.

10. Test the null hypothesis that years of experience and time spent fishing together explain no variation in number of fish

caught among the population of persons who fish.

11. What overall conclusions can you draw from this analysis?

 

 

Click here to see answers to these problems

 

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