Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10:00 - 10:50 Mondays, Wednesdays.

Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10: :50 Mondays, Wednesdays & Fridays. Welcome

Homework Assignments Homework Assignment No homework
Just study for Exam 3

Before next exam (November 18th)
Please read chapters in OpenStax textbook Please read Chapters 2, 3, and 4 in Plous Chapter 2: Cognitive Dissonance Chapter 3: Memory and Hindsight Bias Chapter 4: Context Dependence

Lab sessions Everyone will want to be enrolled
in one of the lab sessions Labs continue this week Project 4

This lab builds on the work we did in our very first lab
This lab builds on the work we did in our very first lab. But now we are using the correlation for prediction. This is called regression analysis

Remember, it never will be if the observed t is less than one
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 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

or decrease level of confidence
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 will not affect level of aggression
Two-tail True 48 2.011 Type of cartoon will not affect level of aggression Type of cartoon will 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

9 7 14 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 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, million dollars for the Westpark neighborhood and 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 6.1 3.35 Yes 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) 42 58 50 ± (1.96)(4) 42.16 57.84
50 ± (7.84)

Winnie found an observed F ratio of .9, what should she conclude?
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 c. Not enough info is given correct

Winnie found an observed z of .74, what should she conclude?
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 c. Not enough info is given correct x x small observed z score small observed z score

Winnie found an observed t of .04, what should she conclude?
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 correct x small observed t score

F(4, 25) = 3.12; p < 0.05 Let’s try one
How many observations within each group? Let’s try one 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 < In this study there were __ types of solar cells and __ total observations in the whole study? a. 4; 25 b. 5; 30 c. 4; 30 d. 5; 25 F(4, 25) = 3.12; p < 0.05 correct # groups - 1 # scores - # of groups # scores - 1

F(4, 25) = 3.12; p < 0.05 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 < 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 Observed F bigger than Critical F p < .05

F(4, 25) = 3.12; p < 0.05 Let’s try one
An ANOVA was conducted comparing different types of solar cells. The analysis was completed using an alpha of But Julia now wants to know if she can reject the null with an alpha of at 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

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 .

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 d. 25 correct .

a. reject the null hypothesis b. not reject the null hypothesis
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 = We should: a. reject the null hypothesis b. not reject the null hypothesis correct 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 d. Eastpark correct

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

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 b c d

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 < What should we conclude? a. we rejected the null hypothesis b. we did not reject the null hypothesis correct F(4, 45) = 9.49; p < 0.01

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 < But Julia now wants to know if she can reject the null with an alpha of at In this study ___ a. we rejected the null hypothesis b. we did not reject the null hypothesis correct F(4, 45) = 9.49; p < 0.01

An ANOVA was conducted comparing ratings for the best
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 .

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 , 41.5 d , 13.8 correct .

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 d. 25 correct .

Let’s try one An ANOVA was conducted comparing ratings for the best Brand of skis (4FRNT, K2, and Rossignol). Alpha = 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 < .05

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

Please fill in the blank a. 3.3541 b. .00635 c. 6.1363 d. 27.00
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 b c d correct

a. The critical F is 3.89; we should reject the null
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 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 d. 3; 80 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) 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 d correct

The critical F ratio a b c d 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 c. p < 0.5 d. both a and c are true 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 observed F is 2 and the critical F ratio is F(2, 30) = ___; n.s. Please fill in the blank a b. 1.3 c. 30 d. 40 correct

a. There is a significant difference t(98) = 2.25; p <0.01
Let’s try one 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 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’ 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 t-test was calculated and there is a significant difference in productivity between the two groups t(278) = 3.64; p < 0.05 A t-test was calculated and there is no significant difference in productivity between the two groups t(278) = 3.64; n.s. A t-test was calculated and there is a significant difference in productivity between the two groups t(280) = 3.64; p < 0.05 A t-test was calculated and there is no significant difference in productivity between the two groups t(280) = 3.64; n.s. Let’s try one correct

a. Theodora found a significant difference between men and women’s
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. 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. Let’s try one correct

Which of the following would represent a one-tailed test?
. . 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

Careful with “exceeds”
Which of the following represents a significant finding: a. p < 0.05 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 correct Careful with “exceeds”

a. Bankers spent significantly more time in front of their
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

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 c d. .004 e correct

a. 10 bankers were measured; 8 retailers were measured
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 c. There is not enough information correct

A table of t-test results
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 results 57

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?
As n ↑ x will approach µ b. As n ↑ curve will approach normal shape c. As n ↑ curve variability gets bigger correct As n ↑ d.

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

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

A Type I Error would claim that:
Which would be a Type II error? 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 correct

He concluded p < 0.05 what does this mean?
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

a. This is a one-tailed test b. This is a two-tailed test
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. 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

Which of the following is best describes this study?
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

Which of the following is best describes his results?
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

Which of the following is best describes his results?
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

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 b. true experiment c. correlational study correct 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

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 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 correct Let’s try one

Let’s try one c. a. d. b. Relationship between movie times and
amount of concession purchases. 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 Matinee Evening Concession purchase a. c. Concession purchase Movie Times correct Movie Times Concession purchase d. Movie Time Concession b. 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 ANOVA d. two-way ANOVA correct

Let’s try one Relationship between GPA and 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 b. t-test c. one-way ANOVA d. two-way ANOVA correct GPA Starting Salary 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 Two-tailed α = 0.05 Significance level = .05 α = 0.01 Significance level = .01 5% 1% 2.5% .5% 2.5% .5% -1.64 or +1.64 A -1.96 or +1.96 B Hint: Possible values 1.64 1.96 2.33 2.58 -2.33 or +2.33 C -2.58 or +2.58 D

Thank you! See you next time!!

Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10:00 - 10:50 Mondays, Wednesdays.

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Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10:00 - 10:50 Mondays, Wednesdays.

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Presentation on theme: "Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10:00 - 10:50 Mondays, Wednesdays."— Presentation transcript:

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