2. Effects: Example 1 20 15 10 5 Low High Variable 2

3. Effects: Example 1 20 15 10 5 Low High Variable 2 Variable 1 (Low)

4. Effects: Example 1 20 15 10 5 Low High Variable 2 Variable 1(High) Variable 1 (Low)

5. 20 15 10 5 Low High Variable 2 Effects: Example 2

6. 20 15 10 5 Low High Variable 2 Effects: Example 2 Variable 1 (Low)

7. 20 15 10 5 Low High Variable 2 Effects: Example 2 Variable 1 (High) Variable 1 (Low)

8. Interaction Effects Defined: dependent variable effects from independent variables taken together Forms: Ordinal (in the same direction as the main effects of variables involved) Disordinal (not in the same direction as the main effects of the variables involved)

9. Interpreting Ordinal Interactions acceptable to look at the independent variables separately permissible to interpret main effects for independent variables involved in the interaction

10. 20 15 10 5 Low High Variable 1 Effects: Example 3

11. 20 15 10 5 Low High Variable 1 Effects: Example 3 Variable 2 (Low)

12. 20 15 10 5 Low High Variable 1 Effects: Example 3 Variable 2 (Low) Variable 2 (High)

13. Interpreting Disordinal Interactions must look at both independent variables together not permissible to interpret main effects for independent variables involved in the interaction

14. 20 15 10 5 Low High Variable 2 Effects: Example 4

15. 20 15 10 5 Low High Variable 2 Effects: Example 4 Variable 1 (Low)

16. 20 15 10 5 Low High Variable 2 Effects: Example 4 Variable 1 (High) Variable 1 (Low)

17. 20 15 10 5 Low High Variable 2 Effects: Example 5

18. 20 15 10 5 Low High Variable 2 Effects: Example 5 Variable 1 (Low)

19. 20 15 10 5 Low High Variable 2 Effects: Example 5 Variable 1 (Low) Variable 1 (High)

20. 20 15 10 5 Low High Variable 2 Effects: Example 6

21. 20 15 10 5 Low High Variable 2 Effects: Example 6 Variable 1 (Low)

22. 20 15 10 5 Low High Variable 2 Effects: Example 6 Variable 1 (High) Variable 1 (Low)

23. Computing Sampling Error Measurement Hypothesis Testing Decisions Types of Statistical tests

24. Confidence Intervals for Proportions Slide 11.1A

25. Confidence Intervals for Proportions Slide 11.1B

26. Confidence Intervals for Proportions Slide 11.1C

27. Confidence Intervals for Proportions Slide 11.1

28. Confidence Interval Example Slide 11.2A

29. Confidence Interval Example Slide 11.2B

30. Confidence Interval Example Slide 11.2

31. Slide 11.3A

32. Slide 11.3B

33. Slide 11.3C

34. One is 90% confident that the proportion of the population that is displeased is equal to.7 (seventy percent), plus or minus.23 (twenty-three percent) Slide 11.3

35. Effects on Confidence Interval If: Sample size is increased to 100:.07 Confidence Interval at 95%:.27 Confidence Interval at 99%:.46 Slide 11.4

36. Selecting a Sample Size Study Objectives Time Limits Cost Data Analysis

37. Computing Sampling Error Measurement Hypothesis Testing Decisions Types of Statistical tests

38. Nominal Level Measurement numbers used as ways to identify or name categories numbers do not indicate degrees of a variable but simple groupings of variables equivalent to qualitative data Slide 8.1

39. Ordinal Level Measurement uses rank order to determine differences measures whether items are “greater than” or “less than” other items identifies relations of measured items to each other Slide 8.2

40. Interval Level Measurement distances between measured items are identified by a matter of degree allows meaningful arithmetic to be applied measures whether items are “greater than” or “less than” other items permits identifying the ratio of intervals to each other Slide 8.3

41. Ratio Level Measurement distances between measured items are identified by a matter of degree –a true quantitative scale and includes an “absolute zero” allows meaningful arithmetic to be applied measures whether items are “greater than” or “less than” other items permits identifying the ratio of intervals to each other Slide8.4

42. Computing Sampling Error Measurement Hypothesis Testing Decisions Types of Statistical tests

43. Actual Condition H 0 is is False H 0 is true

44. Actual Condition H 0 is is False H 0 is true Reject H 0 Do Not Reject H 0

45. Actual Condition H 0 is is False H 0 is true Reject H 0 Do Not Reject H 0 Correct Decision (power)

46. Actual Condition H 0 is is False H 0 is true Reject H 0 Do Not Reject H 0 Correct Decision (power) Type I Error ( a risk)

47. Actual Condition H 0 is is False H 0 is true Reject H 0 Do Not Reject H 0 Correct Decision (power) Type I Error ( a risk) Type II Error ( b risk)

48. Actual Condition H 0 is is False H 0 is true Reject H 0 Do Not Reject H 0 Correct Decision (power) Type I Error ( a risk) Type II Error ( b risk) Correct decision

49. Computing Sampling Error Measurement Hypothesis Testing Decisions Types of Statistical tests

50. One Sample t Test Slide 13.1

51. An Example A communicologist developed a new way to teach statistical methods. One class was given the new method and their scores for the semester were tallied. The other method was retained for another class. Samples of students were taken from each clasan Exampled Current Method New Method 85 92 89 81 90 93 81 87 78 83 79 81 The total number of points possible for the course was 100.

52. Null Hypothesis for Two Sample t Test Slide 13.2

53. t Test for Independent Samples Slide 13.3

54. Finding the Critical Region of t  -2.2282.228

56. Agenda Hypothesis Testing Decisions t tests ANOVA chi square

57. Comparing More than Two Means Mean AMean BMean C Slide 14.1

58. Analysis of Variance Null Hypothesis Slide 14.2

59. Analysis of Variance Slide 14.3A

60. 18 40 62 60 Public Speaking Take Don’t Take international students national students Slide 14.6A Chi Square Example

61. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 Slide 14.6B Chi Square Example

62. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 58 122 Slide 14.6 Chi Square Example

63. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 58 122 25.52 Slide 14.7A Chi Square Example

64. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 58 122 25.52 Slide 14.7B Chi Square Example

65. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 58 122 25.52 32.48 Slide 14.7C Chi Square Example

66. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 58 122 25.5253.68 32.48 Slide 14.7D Chi Square Example

67. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 58 122 25.5253.68 32.4868.32 Slide 14.7E Chi Square Example

68. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 58 122 25.5253.68 32.4868.32 Slide 14.7F Chi Square Example

69. 18 40 62 60 Public Speaking Take Don’t Take international students national students 80 100 58 122 25.5253.68 32.4868.32 Slide 14.7 Chi Square Example