Data Note: This data set will also be used for assignment 3#. Ignore the column entitled cov for this

Data

Note: This data set will also be used for assignment 3#. Ignore the column entitled cov for this assignment ( #2 ) . However it will be used for assignment #3 so it would be useful to save this data file.

	S core (Y)	Treatment (a) (1=reading, 2= cohort, 3=on-line)	Gender (b) (1=M, 2=F)	Average Weekly Study Time (c)
1	65.00	1	1	5.00
2	78.00	1	1	7.00
3	71.00	1	1	6.00
4	61.00	1	1	6.00
5	64.00	1	1	7.00
6	72.00	1	2	8.00
7	74.00	1	2	7.00
8	78.00	1	2	8.00
9	71.00	1	2	8.00
10	76.00	1	2	7.00
11	86.00	2	1	8.00
12	84.00	2	1	8.00
13	87.00	2	1	7.00
14	91.00	2	1	7.00
15	85.00	2	1	8.00
16	91.00	2	2	9.00
17	97.00	2	2	9.00
18	98.00	2	2	9.00
19	92.00	2	2	8.00
20	97.00	2	2	9.00
21	58.00	3	1	6.00
22	45.00	3	1	4.00
23	47.00	3	1	5.00
24	49.00	3	1	5.00
25	44.00	3	1	5.00
26	60.00	3	2	6.00
27	65.00	3	2	6.00
28	72.00	3	2	7.00
29	70.00	3	2	7.00
30	72.00	3	2	7.00

SPSS Routine to use for first analysis involving b as the fixed factor :

Analyze
General Liner Model
- Univariate
  
  dependent = score
  fixed factors = gender b
- Options
  OVERALL > Display means for
  Gender b
  √ Compare main effects
  
  Display
  √ descriptive statistics
  √ observed power
  √ parameter estimates
  Continue
- Post HOC
  Gender b>Post HOC tests for
  √ LSD
  Continue
- OK

SPSS Routine to use for analysis involving gender b as the fixed factor:

Same as above except substitute a for b

Questions for first analysis involving b (gender) as the fixed factor:

1. (L2) What is the mean of b1 (males) and the 95% CI for that mean? Explain how to interpret that CI.

2. (L2) Explain the null hypothesis for this analysis (Gender).

3. ((L2) Explain would it would mean for the null hypothesis to be rejected at the .05 level.

4. (L2) Write the prediction equation for score (Y) based on this analysis.

5. (L3) Explain what the intercept in the equation tells you.

6. (L3) Explain what the regression coefficient tells you?

7. (L3) In the Pairwise Comparisons table, explain what the 95% Confidence Interval for Difference tells you. Also explain how your interpretation compares with the overall significance level for b (gender) in the table for Tests of Between-Subjects Effects.

8. (L3) What is the predicted y score for someone in group b1 (males)? Show how you computed the answer using the prediction equation from question 4.

Questions for second analysis involving a (Treatment) as the fixed factor:

9. (L2) What is the mean of a1 (reading) and the 95% CI for that mean? (see the Estimates box) Explain what the confidence interval tells you.

10. (L2) Explain the null hypothesis for this analysis (Treatment)

11. (L2) Explain would it would mean for the null hypothesis for factor a (treatment) to be rejected at the .05 level?

12. (L2) What is the stated significance level for factor a ? Explain what this means in terms of the null hypothesis making specific reference to the means for a1 (reading), a2 (cohort), and a3 (on-line) and the significance levels of .05.

13 (L2) Write the prediction equation for score (Y) based on this analysis.

14. (L3) Explain what the intercept in the equation tells you.

15. (L3) Which of the following contrasts are significant at the .05 level and explain how you know by examining the 95% CIs for these contrasts?

Reading (a1) vs. Cohort (a2)
Reading (a1) vs. On-line (a3)
Cohort (a2) vs. On-line (a3)

16. (L3) Explain what the regression coefficient for a1 (reading) tells you.

17. (L3) Explain what the regression coefficient for a2 (cohort) tells you.

18. (L3) What is the predicted y score for someone in group a1 (reading)? Show how you computed the answer using the prediction equation.

19. (L3) Using the equations on the top of page 313 of Cohen, explain why all the regression weights are 0 for B1, B2, and B3 when trying to predict Y for the protestant group.

Price: $21.76

Solution: The downloadable solution consists of 12 pages, 976 words and 7 charts.
Deliverable: Word Document