2. Lecturer’s desk INTEGRATED LEARNING CENTER ILC 120 Screen 11 10 2 1 98 7 6 5 13 12 15 14 17 16 19 18 4 3 Row A Row B Row C Row D Row E Row F Row G Row H Row I Row J Row K Row L Computer Storage Cabinet Cabinet Table 20 11 10 2 1 9 8 7 6 5 21 20 23 22 25 24 27 26 4 3 28 13 12 14 16 15 17 18 19 11 10 2 1 9 8 7 6 5 21 20 23 22 25 24 26 4 3 13 12 14 16 15 17 18 19 11 10 2 1 9 8 7 6 5 21 20 23 22 25 24 26 4 3 13 12 14 16 15 17 18 19 11 10 2 1 9 8 7 6 5 21 20 23 22 25 24 27 26 4 3 28 13 12 14 16 15 17 18 19 29 11 10 2 1 9 8 7 6 5 21 20 23 22 25 24 27 26 4 3 28 13 12 14 16 15 17 18 19 11 10 2 1 9 8 7 6 5 21 20 23 22 25 24 27 26 4 3 13 12 14 16 15 17 18 19 11 10 2 1 9 8 7 6 5 21 20 23 22 25 24 26 4 3 13 12 14 16 15 17 18 19 11 10 2 1 9 8 7 6 5 21 20 23 22 25 24 4 3 13 12 14 16 15 17 18 19 11 10 2 1 9 8 7 6 5 21 20 23 22 24 4 3 13 12 14 16 15 17 18 19 11 10 2 1 9 8 7 6 5 21 20 23 22 4 3 13 12 14 16 15 17 18 19 11 10 9 8 7 6 5 4 3 13 12 14 16 15 17 18 19 broken desk

3. Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Fall, 2014 Room 120 Integrated Learning Center (ILC) 10:00 - 10:50 Mondays, Wednesdays & Fridays. http://www.youtube.com/watch?v=oSQJP40PcGI

4. Reminder A note on doodling

5. Schedule of readings Before next exam (November 21 st ) Please read chapters 7 – 11 in Ha & Ha Please read Chapters 2, 3, and 4 in Plous Chapter 2: Cognitive Dissonance Chapter 3: Memory and Hindsight Bias Chapter 4: Context Dependence

6. No homework due – Friday (November 21 st ) Just work on ANOVA projects Prepare for Exam 3

7. Labs continue this week with exam 3 review

8. By the end of lecture today 11/19/14 Use this as your study guide Two-way Analysis of Variance (ANOVA) Interpreting patterns of results Main effects Interactions Review Exam 3

9. Extra Credit - Due November 24 th - There are five parts 1. A one page report of your design (includes all of the information from the writing assignment) Describe your experiment: what is your question / what is your prediction? State your Independent Variable (IV), how many levels there are, and the operational definition State your Dependent Variable (DV), and operational definition How many participants did you measure, and how did you recruit (sample) them Was this a between or within participant design (why?) 2. Gather the data Try to get at least 10 people (or data points) per level If you are working with other students in the class you should have 10 data points per level for each member of your group 3. Input data into Excel (hand in data) 4. Complete ANOVA analysis hand in ANOVA table 5. Statement of results (see next slide for example) and include a graph of your means (just like we did in the homework) This will be graded by attention to detail, creativity and interest of topic

10. One way analysis of variance Variance is divided Total variability Within group variability (error variance) Between group variability (only one factor) Remember, 1 factor = 1 independent variable (this will be our numerator – like difference between means) Remember, error variance = random error (this will be our denominator – like within group variability Remember, one-way = one IV

11. Remember, factor = independent variable Two-way analysis of variance Variance is divided further Total variability Within group variability Between group variability Factor A Variability Factor B Variability Interaction Variability Remember, within group variability = error variability = random error Remember, two-way = two IV Number of cookies sold NoneBikeHawaii trip Elementary College

12. Main effect of A? Main effect of B? Interaction? Significant Fs? Dependent Variable Factor A A1A2 Factor B B1 B2 Dependent Variable Factor A A1A2 Factor B B1 B2 Yes, interaction No main effect of A No main effect of B No interaction Yes main effect of A Yes main effect of B

13. Main effect of A? Main effect of B? Interaction? Significant Fs? Dependent Variable Factor A A1A2 Factor B B1 B2 Dependent Variable Factor A A1A2 Factor B B1 B2 Yes, interaction No main effect of A Yes main effect of B No interaction Yes main effect of A No main effect of B

14. Let’s try one For the independent variable plotted on the x-axis a. there is a main effect b. There is not a main effect Dependent Variable Factor A A1A2 Factor B B1 B2

15. Dependent Variable Factor A A1A2 Factor B B1 B2 For the independent variable plotted with the two lines a. there is a main effect b. there is not a main effect

16. Let’s try one For the two independent variables a. there is an interaction b. there is not an interaction Dependent Variable Factor A A1A2 Factor B B1 B2

17. Let’s try one In a two-way ANOVA we have one dependent variable and two independent variables. Which of the following graphs shows no interaction Amount of Activity Adderall NoYes ADHD Control Weight Calories LowHigh High Exercise Low Exercise Cookies Sold Incentives NoneHawaii CollegeElementary Activity Another Male Spray SprayNo Spray Male Female A B C D a. A b. B c. C d. D correct

18. Let’s try one In a two-way ANOVA we have one dependent variable and two independent variables. This graph shows Weight Calories LowHigh High Exercise Low Exercise a. A main effect of exercise, but no main effect of calories b. A main effect of exercise, and a main effect of calories c. No main effect of exercise, and no main effect of calories d. No main effect of exercise, a main effect of calories correct

19. Let’s try one In a two-way ANOVA we have one dependent variable and two independent variables. This graph shows a. A main effect of incentive, but no main effect of age b. A main effect of incentive, and a main effect of age c. No main effect of incentive, and no main effect of age d. No main effect of incentive, a main effect of age Cookies Sold Incentives NoneHawaii CollegeElementary correct

20. Let’s try one In a 2 x 2 ANOVA there are how many tests of significance? (or how many “F”s are calculated?) a. 1 b. 2 c. 3 d. 4 correct

21. Hand in Writing Assignment

22. Let’s try one In a one-way ANOVA we have three types of variability. Which picture best depicts the between group variability? a. Figure 1 b. Figure 2 c. Figure 3 d. All of the above 1. 2. 3. correct

23. Let’s try one Winnie found an observed z of.74, what should she conclude? (Hint: notice that.74 is less than 1) a. Reject the null hypothesis b. Do not reject the null hypothesis c. Not enough info is given small observed z score x x If your observed z is within one standard deviation of the mean, you will never reject the null correct

24. Let’s try one Winnie found an observed t of.04, what should she conclude? (Hint: notice that.04 is less than 1) a. Reject the null hypothesis b. Do not reject the null hypothesis c. Not enough info is given small observed t score x correct

25. Let’s try one Winnie found an observed F ratio of.02, what should she conclude? a. Reject the null hypothesis b. Do not reject the null hypothesis c. Not enough info is given 1. 2. 3. correct

26. Let’s try one An ANOVA was conducted comparing “best racquet” scores for different types of tennis racquets. The results were: F(4, 45) = 9.49; p < 0.05. In this study there were __ types of tennis racquets and __ total observations in the whole study? a. 4; 45 b. 5; 50 c. 4; 50 d. 5; 45 # groups - 1 # scores - # of groups # scores - 1 F(4, 45) = 9.49; p < 0.01 How many observations within each group? correct

27. Let’s try one An ANOVA was conducted comparing “best racquet” scores for different types of tennis racquets. The results were: F(4, 45) = 9.49; p < 0.05. What should we conclude? a. we rejected the null hypothesis b. we did not reject the null hypothesis F(4, 45) = 9.49; p < 0.01 correct

28. Let’s try one An ANOVA was conducted comparing “best racquet” scores for different types of tennis racquets. The results were: F(4, 45) = 9.49; p < 0.05. But Julia now wants to know if she can reject the null with an alpha of at 0.01. In this study ___ a. we rejected the null hypothesis b. we did not reject the null hypothesis F(4, 45) = 9.49; p < 0.01 correct

29. Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4FRNT, K2, and Rossignol). For each brand of ski we rated 10 skis. Degrees of freedom between is _____; degrees of freedom within is ____ a. 30; 3 b. 3; 30 c. 27; 2 d. 2; 27. correct

30. Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4FRNT, K2, and Rossignol). For each brand of ski we rated 10 skis. Mean Square between is _____; Mean Square within is ____ a. 6.9, 1.5 b. 1.5, 6.9, c. 13.8, 41.5 d. 41.5, 13.8. correct

31. Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4FRNT, K2, and Rossignol). For each brand of ski we rated 10 skis. The F ratio is: a..25 b. 1 c. 4.51 d. 25. correct

32. An ANOVA was conducted comparing ratings for the best Brand of skis (4FRNT, K2, and Rossignol). Alpha = 0.05. Please complete this ANOVA table. We should: a. reject the null hypothesis b. not reject the null hypothesis Let’s try one p <.05 Observed F bigger than Critical F correct

33. An ANOVA was conducted comparing ratings for the best Brand of skis (4FRNT, K2, and Rossignol). Alpha = 0.01. Please complete this ANOVA table. We should: a. reject the null hypothesis b. not reject the null hypothesis Let’s try one p NOT <.01 Observed F bigger than Critical F correct

34. An ANOVA was conducted comparing ratings for the best Brand of skis (4FRNT, K2, and Rossignol). The best rated brand of skis was ____ a. 4FRNT b. K2 c. Rossignol Let’s try one correct

35. an alpha of 0.01 Tasi is a small business owner who wanted to know whether her advertising campaign would make a difference in the average amount of money spent by her customers. She has two businesses, one in California and one in Florida. She completed an ad campaign in California, but had no advertising campaign in Florida. She then compared sales and completed a t-test using an alpha of 0.01. The results are presented in this table. Which of the following best describes the results of her experiment: a. There is a significant difference t(98) = 2.25; p <0.01 b. There is not a significant difference t(98) = 2.25; p <0.01 c. There is a significant difference t(98) = 2.25; n.s. d. There is not a significant difference t(98) = 2.25; n.s. Let’s try one correct

36. Let’s try one Theodora is researcher who compares how different companies address workers’ quality of life and general productivity. She created a questionnaire that measured these two constructs and gave the test to 140 men and 140 women. Please refer to this table to answer the following question: Which of the following best describe Theodora’s findings on worker productivity? a.A t-test was calculated and there is a significant difference in productivity between the two groups t(278) = 3.64; p < 0.05 b.A t-test was calculated and there is no significant difference in productivity between the two groups t(278) = 3.64; n.s. c.A t-test was calculated and there is a significant difference in productivity between the two groups t(280) = 3.64; p < 0.05 d.A t-test was calculated and there is no significant difference in productivity between the two groups t(280) = 3.64; n.s. correct

37. Let’s try one Refer again to Theodora’s findings presented on the table. Let’s assume for this question that Theodora set her alpha at 0.01, which of the following is true? a. Theodora found a significant difference between men and women’s quality of life, but not between men and women’s productivity. b.Theodora found a significant difference between men and women’s productivity, but not between men and women’s quality of life measures c. Theodora found a significant difference between men and women for both productivity and quality of life measures. d. Theodora found no significant difference between men and women for neither productivity nor quality of life measures. correct

38. .. Which of the following would represent a one-tailed test? a. Please test to see whether men or women are taller b. With an alpha of.05 test whether advertising increases sales c. With an alpha of.01 test whether management strategies affect worker productivity d. Does a stock trader’s education affect the amount of money they make in a year? correct

39. Which of the following represents a significant finding: a. p < 0.05 b. critical value exceeds the observed statistic c. the observed z statistic is nearly zero d. we reject the null hypothesis e. Both a and d Careful with “exceeds” correct

40. A t-test was conducted to see whether “Bankers” or “Retailers” spend more time in front of their computer. Which best summarizes the results from this excel output: a. Bankers spent significantly more time in front of their computer screens than Retailers, t(3.5) = 8; p < 0.05 b. Bankers spent significantly more time in front of their computer screens than Retailers, t(8) = 3.5; p < 0.05 c. Retailers spent significantly more time in front of their computer screens than Bankers, t(3.5) = 8; p < 0.05 d. Retailers spent significantly more time in front of their computer screens than Bankers, t(8) = 3.5; p < 0.05 e. There was no difference between the groups correct

41. A t-test was conducted to see whether “Bankers” or “Retailers” spend more time in front of their computer. Which critical t would be the best to use a. 3.5 b. 1.859 c. 2.306 d..004 e..008 Let’s try one correct

42. A t-test was conducted to see whether “Bankers” or “Retailers” spend more time in front of their computer. How many bankers and retailers were measured a. 10 bankers were measured; 8 retailers were measured b. 10 bankers were measured; 10 retailers were measured c. 5 bankers were measured; 5 retailers were measured Let’s try one correct

43. Let’s try one An ANOVA was conducted and there appears to be a significant difference in the number of cookies sold as a result of the different levels of incentive F(2, 27) = ___; p < 0.05. Please fill in the blank a. 3.3541 b..00635 c. 6.1363 d. 27.00 correct

44. Let’s try one An ANOVA was conducted and we found the following results: F(3,12) = 3.73 ____. Which is the best summary a. The critical F is 3.89; we should reject the null b. The critical F is 3.89; we should not reject the null c. The critical F is 3.49; we should reject the null d. The critical F is 3.49; we should not reject the null correct

45. Let’s try one Agnes compared the heights of the women’s gymnastics team and the women’s basketball team. If she doubled the number of players measured (but ended up with the same means) what effect would that have on the results? a. the means are the same, so the t-test would yield the same results. b. the means are the same, but the variability would increase so it would be harder to reject the null hypothesis. c. the means are the same, but the variability would decrease so it would be easier to reject the null hypothesis. correct

46. Let’s try one Albert compared the heights of a small sample of 10 women from the women’s gymnastics team to the mean for the whole team (population). This is an example of a one-sample t-test. He found an observed t(9) =.04, what should he do? a. Reject the null hypothesis b. Do not reject the null hypothesis c. There is not enough information correct

47. A table of t-test results How many of these t-tests reach significance with alpha of 0.05? a. 1b. 2c. 3d. 4 correct

48. An advertising firm wanted to know whether the size of an ad in the margin of a website affected sales. They compared 4 ad sizes (tiny, small, medium and large). They posted the ads and measured sales. This is an example of a _____. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA Relationship between advertising space and sales correct

49. According to the Central Limit Theorem, which is false? As n ↑ As n ↑ x will approach µ As n ↑ curve will approach normal shape As n ↑ curve variability gets bigger a. b. c. d. correct

50. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. Which of the following is true? a. The IV is gender while the DV is time to finish a race b. The IV is time to finish a race while the DV is gender correct

51. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. Which of the following is true? a. The null hypothesis is that there is no difference in race times between the genders b. The null hypothesis is that there is a difference between the genders correct

52. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. A Type I Error would claim that: a. There is a difference when in fact there is b. There is a difference when in fact there isn’t one c. There is no difference when in fact there isn’t one d. There is no difference when in fact there is a difference Which would be a Type II error? correct

53. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. He concluded p < 0.05 what does this mean? a. There is a significant difference between the means b. There is no significant difference between the means correct

54. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. Which of the following is true? a. This is a one-tailed test b. This is a two-tailed test correct

55. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. Which of the following is true? a. This is a quasi, between participant design b. This is a quasi, within participant design a. This is a true, between participant design b. This is a true, within participant design correct

56. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. Which of the following is best describes this study? a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA correct

57. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. Which of the following is best describes his results? a. t(198) = 2.38; p < 0.05 b. t(198) = 2.38; ns c. t(198) = 1.97; p < 0.05 d. t(198) = 1.97; ns correct

58. Let’s try one Albert compared the race times of 20 male and female jockeys for race horses. He wanted to know who averaged faster rides. Which of the following is best describes his results? a. t(198) = 2.38; p < 0.01 b. t(198) = 2.38; ns c. t(198) = 1.97; p < 0.01 d. t(198) = 1.97; ns correct

59. An ANOVA was conducted comparing which type of horse is the fastest (Arabians, Thoroughbreds, or Quarter Horses). We measured how long it took to finish the race. We measured 11 of each type of horse (33 altogether) Please complete this ANOVA table. Degrees of freedom between is _____; degrees of freedom within is ____ a. 30; 2 b. 2; 30 c. 80; 3 d. 3; 80 correct

60. An ANOVA was conducted comparing which type of horse is the fastest (Arabians, Thoroughbreds, or Quarter Horses). We measured how long it took to finish the race. We measured 11 of each type of horse (33 altogether) Mean Square Between is ____ while Mean Square Within is ______ a. 80; 2 b. 2; 80 c. 30; 40 d. 40; 30 correct

61. An ANOVA was conducted comparing which type of horse is the fastest (Arabians, Thoroughbreds, or Quarter Horses). We measured how long it took to finish the race. We measured 11 of each type of horse (33 altogether) Please complete this ANOVA table. The F ratio is a..75 b. 1.3 c. 1.5 d. 1.75 correct

62. The critical F ratio a. 2.84 b. 2.92 c. 3.23 d. 3.32 correct

63. The observed F is 1.3 and the critical F ratio is 3.32. What should we conclude? a. reject the null hypothesis b. do not reject the null hypothesis c. p < 0.5 d. both a and c are true correct

64. An ANOVA was conducted comparing which type of horse is the fastest (Arabians, Thoroughbreds, or Quarter Horses). We measured how long it took to finish the race. We measured 11 of each type of horse (33 altogether) Please complete this ANOVA table. The observed F is 2 and the critical F ratio is 3.32. F(2, 30) = ___; n.s. Please fill in the blank a. 3.32 b. 1.3 c. 30 d. 40 correct

65. Let’s try one An ANOVA was conducted comparing home prices in four neighborhoods (Southpark, Northpark, Westpark, Eastpark). For each neighborhood we measured the price of four homes. Please complete this ANOVA table. The F ratio is: a..25 b. 1 c. 4 d. 25. correct

66. An ANOVA was conducted comparing home prices in four neighborhoods (Southpark, Northpark, Westpark, Eastpark). For each neighborhood we measured the price of four homes. Please complete this ANOVA table, alpha = 0.05. We should: a. reject the null hypothesis b. not reject the null hypothesis Let’s try one p <.05 Observed F bigger than Critical F correct

67. An ANOVA was conducted comparing home prices in four neighborhoods (Southpark, Northpark, Westpark, Eastpark). For each neighborhood we measured the price of four homes. The most expensive neighborhood was the ____ neighborhood a. Southpark b. Northpark c. Westpark d. Eastpark Let’s try one correct

68. An ANOVA was conducted comparing home prices in four neighborhoods (Southpark, Northpark, Westpark, Eastpark). For each neighborhood we measured the price of four homes. Please complete this ANOVA table. The best summary statement is: a. F(3, 12) = 4.0; n.s. b. F(3, 12) = 4.0; p < 0.05 c. F(3, 12) = 3.49; n.s. d. F(3, 12) = 3.49; p < 0.05 correct

69. An advertising firm wanted to know whether the size of an ad in the margin of a website affected sales. They compared 4 ad sizes (tiny, small, medium and large). They posted the ads and measured sales. This is an example of a _____. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA Relationship between advertising space and sales correct

70. Victoria was also interested in the effect of vacation time on productivity of the workers in her department. In her department some workers took vacations and some did not. She measured the productivity of those workers who did not take vacations and the productivity of those workers who did (after they returned from their vacations). This is an example of a _____. a. quasi-experiment b. true experiment c. correlational study Let’s try one correct

71. Ian was interested in the effect of incentives for girl scouts on the number of cookies sold. He randomly assigned girl scouts into one of three groups. The three groups were given one of three incentives and he looked to see who sold more cookies. The 3 incentives were: 1) Trip to Hawaii, 2) New Bike or 3) Nothing. This is an example of a ___. a. quasi-experiment b. true experiment c. correlational study Let’s try one correct

72. Ian was interested in the effect of incentives and age for girl scouts on the number of cookies sold. He randomly assigned girl scouts into one of three groups. The three groups were given one of three incentives and he looked to see who sold more cookies. The 3 incentives were: 1) Trip to Hawaii, 2) New Bike or 3) Nothing. He also measured their age. This is an example of a ___. a. quasi-experiment b. true experiment c. correlational study d. mixed design Let’s try one correct

73. Marietta is a manager of a movie theater. She wanted to know whether there is a difference in concession sales for afternoon (matinee) movies vs. evening movies. She took a random sample of 25 purchases from the matinee movie (mean of $7.50) and 25 purchases from the evening show (mean of $10.50). She compared these two means. This is an example of a _____. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA Relationship between movie times and amount of concession purchases. Let’s try one correct

74. Marietta is a manager of a movie theater. She wanted to know whether there is a difference in concession sales for afternoon (matinee) movies and evening movies. She took a random sample of 25 purchases from the matinee movie (mean of $7.50) and 25 purchases from the evening show (mean of $10.50). Which of the following would be the appropriate graph for these data Relationship between movie times and amount of concession purchases. Let’s try one Matinee Evening Concession purchase a. Movie Time Concession b. Movie Times Concession purchase d. c. Concession purchase Movie Times correct

75. Pharmaceutical firm tested whether fish-oil capsules taken daily decrease cholesterol. They measured cholesterol levels for 30 male subjects and then had them take the fish-oil daily for 2 months and tested their cholesterol levels again. Then they compared the mean cholesterol before and after taking the capsules. This is an example of a _____. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA Relationship between daily fish-oil capsules and cholesterol levels in men. correct

76. Elaina was interested in the relationship between the grade point average and starting salary. She recorded for GPA. and starting salary for 100 students and looked to see if there was a relationship. This is an example of a _____. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA Relationship between GPA and starting salary Let’s try one Relationship between GPA and Starting salary GPA Starting Salary correct

77. -1.64 or +1.64 Critical z values One-tailedTwo-tailed α = 0.05 Significance level =.05 α = 0.01 Significance level =.01 -1.96 or +1.96 -2.33 or +2.33 -2.58 or +2.58 5% 2.5% 1%.5% Match each level of significance to each situation. Which situation would be associated with a critical z of 1.96? a. A b. B c. C d. D A B CD Hint: Possible values 1.64 1.96 2.33 2.58

78. Let’s try one In a one-way ANOVA we have three types of variability. Which picture best depicts the random error variability (also known as the within variability)? a. Figure 1 b. Figure 2 c. Figure 3 d. All of the above 1. 2. 3. correct