1. Final exam practice questions (answers at the end)

2. Question 1 You will have to write two relatively brief, one-paragraph answers: 1. General question about hypotheses 2. Question about rejecting the null hypothesis Your responses to the above should be based on a thorough understanding of the material in slides 3-7 of the Inferential Stat Intro presentation

3. Question 2 Hypothesis is that alarm systems prevent crime
Question 2 Hypothesis is that alarm systems prevent crime. To test this hypothesis we randomly sampled 120 businesses with an alarm system, and 90 businesses without an alarm system: With an alarm system: 50 were victims of crime, 70 were not victims of crime Without an alarm system: 50 were victims of crime, 40 were not victims of crime. 1-A: State the “null hypothesis” using plain English (2 pts.) 1-B. Draw a table with the Observed frequencies 1-C. Compute the Expected frequencies and place them in a table 1-D. Compute the Chi-Square 1-E. Compute the degrees of freedom df = (r-1) X (c-1) 1-F. Check the table. Do the results support the working hypothesis?

4. Question 3 Are male CJ majors significantly more cynical than female CJ majors? We randomly sampled five males and five females. Here are their test results: Males: 4, 5, 5, 3, 4 Variance (s2): 0.7 Females: 4, 3, 4, 4, 5 Variance (s2): A: State the “null hypothesis” using plain English (2 pts.) 2-B. Pooled sample variance (midpoint between the two variances): _______ 2-C. Standard error of the differences between means ( ): _______ 2-D. t-statistic: ______ 2-E. df (degrees of freedom): _____ df = (n1+n2)-2 2-F. Check the t table. Can you reject the null hypothesis? YES ____ NO ____ 2-G. Justify your answer to 2-F using plain English. Avoid technical terms. Make sure to include the estimated accuracy.

5. Question 4
Hypothesis: Unstructured socializing
and other factors  youth violence
In which model does Age have the greatest effect?
What is its numerical significance?
Use words to explain #2
Use Odds Ratio (same as Exp b) to describe the percentage effect of Age on Violence in Model 1
What happens to Age as it moves from Model 2 to Model 3? What seems most responsible?

6. Answers to practice questions 2-4
(No answers for question 1 - please study the
Inferential stat’s intro slide show, esp. slides 3-7)

7. ANSWERS TO QUESTION 2
Null hypothesis: No significant difference in crime between businesses with and without alarms
Observed frequencies
Expected frequencies
Chi-Square = 3.82
Df = (r-1) X (c-1) = 1
Check the table. Do the results support the working hypothesis? No - Chi-Square must be at least to reject the null hypothesis of no relationship between alarm systems and crime, with only five chances in 100 that it is true

8. ANSWERS TO QUESTION 3
Null hypothesis: No significant difference between cynicism of males and females
Variance for males (provided): 0.7 Variance for females (provided): 0.5
Pooled sample variance = .6
SE of the difference between means = .49 t = .41 df = 8
Check the “t” table. Can you reject the null hypothesis? NO
Describe conclusion using words: The t must be at least 1.86 (one-tailed test) to reject the null hypothesis of no significant difference in cynicism, with only five chances in 100 that it is true.

9. ANSWERS TO QUESTION 4
Hypothesis: Unstructured socializing
and other factors  youth violence
In which model does Age have the greatest effect? Model 1
What is its numerical significance? .001
Use words to explain #2 Less than one chance in 1,000 that the relationship between age and violence is due to chance
Use Odds Ratio (same as Exp b) to describe the percentage effect of Age on Violence in Model 1 For each year that age increases, violence is seventeen percent more likely
What happens to Age as it moves from Model 2 to Model 3? What seems most responsible? Age becomes non-significant. Most likely cause is introduction of variable Deviant Peers (it is the most significant of the four variables introduced in Model 3).