BNAD 276 Statistical Inference in Management Spring 2016

BNAD 276: Statistical Inference in Management Spring 2016 Green sheets

Schedule of readings Before our next exam (April 7 th) Open. Stax Chapters 1 – 12 Plous (2, 3, & 4) Chapter 2: Cognitive Dissonance Chapter 3: Memory and Hindsight Bias Chapter 4: Context Dependence

By the end of lecture today 4/5/16 Analysis of Variance (ANOVA) Constructing brief, complete summary statements Review for Exam 3

Exam 3 – This Thursday, April 7 th Study guide is online Bring 2 calculators (remember only simple calculators, we can’t use calculators with programming functions) Bring 2 pencils (with good erasers) Bring ID Stats Review by Nick and Jonathon When: Wednesday evening April 6 th - 6: 30 – 8: 30 pm Where: Harvill 150 Cost: $5. 00

Homework Assignment No homework Assignment Just study for Exam 3

Yes, p <. 05, reject the null and it is a significant difference No, p is not <. 05, do not reject the null and there is no significant difference Remember, it never will be if the observed t is less than one small observed t score

Decrease variability or decrease level of confidence It is easier to reject the null It gets narrower Easier; use a one-tail test when you have a unidirectional prediction Use a t-test when don’t know population standard deviation and only have sample standard deviation (Same is true for variance or variability)

Type of cartoon Two-tail 48 Level of aggression True 2. 011 Type of cartoon will not affect level of aggression Type of cartoon will not affect aggression when it fact it will Type of cartoon will affect aggression when it fact it will not

Common and rare scores Go down from. 05 to. 01 Mean approaches the true population mean Shape approaches normality Variability goes down No, never reject null if the prediction in a one-tailed test is wrong

14 71. 7142 9 7 The mean test scores were 78 for the men and 79 for the women enrolled in Dr. Rubio’s class. A t-test was conducted and no significant difference was found, t(14) = -0. 23; n. s.

12 3 25 100 4 3. 49 Yes The mean home prices were compared for these four neighborhoods. The average selling price was 65. 5 million dollars in the Southpark neighborhood, 71 million dollars in the Northpark neighborhood, 77. 25 million dollars for the Westpark neighborhood and 74. 75 million dollars for the Eastpark neighborhood. An ANOVA was conducted and a significant main effect was found, F(3, 12) = 4. 00; p < 0. 05.

27 2 40 6. 518 3. 35 6. 1 Yes The mean number of cookies sold was 10 boxes for the girl scouts offered no incentive, 12 boxes for the girl scouts offered a new bike and 14 boxes for girl scouts offered a trip to Hawaii. An ANOVA conducted and a significant main effect was found, F(2, 27) = 6. 14; p < 0. 05

95% Mean ± (z)(standard deviation) 50 ± (1. 96)(4) 50 ± (7. 84) 42 42. 16 58 57. 84

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 1. c. Figure 3 correct d. All of the above 2. 3. iew v Re

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 correct c. Figure 3 1. d. All of the above 2. 3. iew v Re

Let’s try one F= Variability between groups Variability within groups Which figure would depict the largest F ratio a. Figure 1 b. Figure 2 correct c. Figure 3 d. All of the above 1. “F ratio” is referring to "observed F” 2. 3. iew v Re

Let’s try one Winnie found an observed F ratio of. 9, what should she conclude? a. Reject the null hypothesis b. Do not reject the null hypothesis correct c. Not enough info is given 1. 2. 3. iew v Re

If your observed z is within one standard deviation of the mean, you will never reject the null 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 correct c. Not enough info is given x x small observed z score iew v Re

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 correct c. Not enough info is given x small observed t score iew v Re

Let’s try one How many observations within each group? An ANOVA was conducted comparing different types of solar cells and there appears to be a significant difference in output of each (watts) F(4, 25) = 3. 12; p < 0. 05. In this study there were __ types of solar cells and __ total observations in the whole study? a. 4; 25 F(4, 25) = 3. 12; p < 0. 05 b. 5; 30 c. 4; 30 correct d. 5; 25 # groups - 1 # scores - # of groups # scores - 1 iew v Re

Let’s try one An ANOVA was conducted comparing different types of solar cells and there appears to be significant difference in output of each (watts) F(4, 25) = 3. 12; p < 0. 05. In this study ___ a. we rejected the null hypothesis correct b. we did not reject the null hypothesis F(4, 25) = 3. 12; p < 0. 05 Observed F bigger than Critical F p <. 05 iew v Re

Let’s try one An ANOVA was conducted comparing different types of solar cells. The analysis was completed using an alpha of 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 correct F(4, 25) = 3. 12; p < 0. 05 Comparison of the Observed F and Critical F Is no longer are helpful because the critical F is no longer correct. We must use the p value p <. 05 p >. 01 iew ev

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. Degrees of freedom between is _____; degrees of freedom within is ____ a. 16; 4 b. 4; 16 c. 12; 3 d. 3; 12 correct . iew ev

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. Mean Square between is _____; Mean Square within is ____ a. 300, 300 b. 100, 100 c. 100, 25 d. 25, 100 correct .

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 correct d. 25 .

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, alpha = 0. 05. We should: a. reject the null hypothesis correct b. not reject the null hypothesis Observed F bigger than Critical F p <. 05

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. The most expensive neighborhood was the ____ neighborhood a. Southpark b. Northpark c. Westpark correct d. Eastpark

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 correct c. F(3, 12) = 3. 49; n. s. d. F(3, 12) = 3. 49; p < 0. 05

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

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 correct b. we did not reject the null hypothesis F(4, 45) = 9. 49; p < 0. 01

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 correct b. we did not reject the null hypothesis F(4, 45) = 9. 49; p < 0. 01

Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4 FRNT, K 2, 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 .

Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4 FRNT, K 2, 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, correct c. 13. 8, 41. 5 d. 41. 5, 13. 8 .

Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4 FRNT, K 2, and Rossignol). For each brand of ski we rated 10 skis. The F ratio is: a. . 25 b. 1 c. 4. 51 correct d. 25 .

Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4 FRNT, K 2, and Rossignol). Alpha = 0. 05. Please complete this ANOVA table. We should: a. reject the null hypothesis correct b. not reject the null hypothesis Observed F bigger than Critical F p <. 05

Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4 FRNT, K 2, and Rossignol). Alpha = 0. 01. Please complete this ANOVA table. We should: a. reject the null hypothesis b. not reject the null hypothesis correct Observed F bigger than Critical F p NOT <. 01

Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4 FRNT, K 2, and Rossignol). The best rated brand of skis was ____ a. 4 FRNT b. K 2 c. Rossignol correct

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 correct d. 27. 00

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 nullcorrect Let’s try one

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 correct d. 3; 80

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

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 correct d. 1. 75

The critical F ratio a. 2. 84 b. 2. 92 c. 3. 23 d. 3. 32 correct

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 correct c. p < 0. 5 d. both a and c are true

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 correct d. 40

Let’s try one Tasi is a small business owner who wanted to know whether 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. correct

Theodora is researcher who compares how different companies address workers’Let’s quality life and general productivity. She created a tryofone 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 correct 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.

Refer again to Theodora’s findings presented on the table. Let’s assume for this question Theodora set her alpha at 0. 01, which of the Let’s that try one 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 correct 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.

. . 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 correct affect worker productivity d. Does a stock trader’s education affect the amount of money they make in a year?

Which of the following represents a significant finding: a. p < 0. 05 correct b. the observed statistic (z score) is not bigger than critical value c. the observed z statistic is nearly zero d. do not reject the null hypothesis Careful with “exceeds”

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 correct 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

Let’s try one 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 correct d. . 004 e. . 008

Let’s try one 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 correct

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

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 correct c. There is not enough information

How many of these t-tests reach significance with alpha of 0. 05? a. 1 b. 2 c. 3 d. 4 correct A table of t-test

Relationship between advertising space and sales 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 correct

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

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 correct b. The IV is time to finish a race while the DV is gender

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 correct b. The null hypothesis is that there is a difference between the genders

Let’s try one Which would be a Type II error? 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. b. c. d. There is a difference when in fact there isn’t one There is no difference when in fact there isn’t one correct There is no difference when in fact there is a difference

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

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

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. b. This is a quasi, between participant design correct This is a quasi, within participant design This is a true, between participant design This is a true, within participant design

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 correct c. one-way ANOVA d. two-way ANOVA

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 correct b. t(198) = 2. 38; ns c. t(198) = 1. 97; p < 0. 05 d. t(198) = 1. 97; ns

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 correct c. t(198) = 1. 97; p < 0. 01 d. t(198) = 1. 97; ns

Relationship between advertising space and sales 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 correct

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 correct b. true experiment c. correlational study Let’s try one

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 correct Let’s try one

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 correct Let’s try one

Relationship between movie times and amount of concession purchases. Marietta is a manager of a movie theater. She wanted to know whethere 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 correct c. one-way ANOVA d. two-way ANOVA Let’s try one

Relationship between movie times and amount of concession purchases. Matinee correct d. Concession b. Evening Concession purchase c. Movie Times Concession purchase a. Concession purchase Marietta is a manager of a movie theater. She wanted to know whethere 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 Movie Times Let’s try one

Relationship between daily fish-oil capsules and cholesterol levels in men. 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 correct ANOVA d. two-way ANOVA

Relationship between GPA and starting salary Starting Salary 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 correct b. t-test c. one-way ANOVA d. two-way ANOVA GPA Relationship between GPA and Starting salary Let’s try one

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 Critical z values One-tailed 5% 1% α = 0. 05 Hint: Possible values 1. 64 1. 96 2. 33 2. 58 Significance level =. 05 α = 0. 01 Significance level =. 01 Two-tailed 2. 5%. 5% -1. 64 or +1. 64 A -1. 96 or +1. 96 C -2. 58 or +2. 58 -2. 33 or +2. 33 B D

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 1. c. Figure 3 correct d. All of the above 2. 3.