Applied Statistics
Data Set A: problems 1-3.
                                             SAT      GPA        SES
SAT    Pearson Correlation             1      0.778       0.232
     Sig. (2-tailed)                         .      0.002        0.71
     N                                   145200    145200    145200
GPA    Pearson Correlation          0.778      1           0.424
     Sig. (2-tailed)                     0.002       .           0.081
     N                                     145200    145200    145200
SES    Pearson Correlation         0.232       0.424        1
     Sig. (2-tailed)                     0.71        0.081        .
     N                                    145200    145200    145200

1. Find r xy  if  SAT = x and GPA = y ?

a. 0.778

b. 0.232

c. 0.002

d. 0.71

2. Which of the following correlations is important(p < .05)?

a. SAT and GPA

b. GPA and SES

c. SAT and SES

d. All the above

3. What is the variance accounted for in SAT due to GPA?

a. 40%

b. 60.5%

c. 5.4%

d. Less than 1%

Research Design A: problems 4-8

A researcher was interested in the effects of sexual arousal on the ability to concentrate, and also wondered if gender and age are important factors or not. The researcher had participants read passages which were low, medium, or high in sexual arousal content. The participants included both males and females and were divided into three age categories (18-24, 25-35, and 36-50 years). After reading the passage, concentration was measured by the proofreading task; researcher measured the number of errors detected on task.

4. What kind of statistical procedure must the researcher use to answer the problems?

a. Standard Deviation

b. Independent Sample t test

c. Correlation

d. Factorial Anova

5. Which of the following are the Independent Variables:

a. Gender, Sexual Arousal, Age

b. Gender, Age, Concentration

c. Sexual Arousal, Age, Concentration

d. Sexual Arousal, Concentration, Gender

6. Which of the following is Dependent Variable

a. Sexual Arousal

b. Gender

c. Concentration

d. Age

7. Which of the following represents  design?

a. 3 x 3 x 2

b. 3 x 3

c. 2 x 3

d. 2 x 3 x 1

8. Which of the following represents the possible interaction?

a. Gender affects concentration

b. Sexual arousal affects concentration

c. Sexual arousal affects concentration but only for males

d. Only high levels of sexual arousal affects concentration

Data Set 2: problems 9-10

Commissioner of the National Hockey League wishes to know if offense (Goals_F), defense (Goals_A) and penalties (Pen_Min) predict winning (Tier).

    Model Summary
Model                        R             R Square    Adjusted R Square    Std. Error of the Estimate
1                            .581(a)          .338              .314                               .966
2                            .728(b)          .531              .496                                .828
3                            .734(c)          .538              .485                                .837

a  Predictors: (Constant), Goals_F

b  Predictors: (Constant), Goals_F, Goals_A

c  Predictors: (Constant), Goals_F, Goals_A, Pen_Min

                                                ANOVA(d)
Model                           Sum of Squares    df      Mean Square     F            Sig.
1    Regression                     13.336           1      13.336           14.290     .001(a)
     Residual                         26.131           28     .933          
     Total                            39.467            29               
2    Regression                     20.945            2      10.473          15.267      .000(b)
     Residual                        18.521            27      .686           
     Total                            39.467            29               
3    Regression                    21.245             3        7.082         10.104      .000(c)
     Residual                       18.222              26     .701          
     Total                           39.467              29

a  Predictors: (Constant), Goals_F

b  Predictors: (Constant), Goals_F, Goals_A

c  Predictors: (Constant), Goals_F, Goals_A, Pen_Min

d  Dependent Variable: Tier

9. If he wants to describe maximum variability (Adjusted R squared) in winning then which one must he choose?

a. Model 1

b. Model 2

c. Model 3

10. How much variability in winning is NOT described by the best model (coefficient of alienation converted to a percentage)?

a. 31.4 %

b. 49.6%

c. 68.6%

d. 50.4%