Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Spring 2017 Room 150 Harvill Building 9:00 - 9:50 Mondays, Wednesdays.

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Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Spring 2017 Room 150 Harvill Building 9:00 - 9:50 Mondays, Wednesdays & Fridays. Welcome http://www.youtube.com/watch?v=oSQJP40PcGI http://www.youtube.com/watch?v=oSQJP40PcGI

A note on doodling

Schedule of readings Before our fourth and final exam (May 1st) OpenStax Chapters 1 – 13 (Chapter 12 is emphasized) Plous Chapter 17: Social Influences Chapter 18: Group Judgments and Decisions

Lab sessions Everyone will want to be enrolled in one of the lab sessions No more labs

By the end of lecture today 4/28/17 Review for Exam 4

Review Sheet

didn’t make a difference it did Get smaller Type of cartoon Level of aggression Two-tail True 48 No difference in level of aggression based on type of cartoon watched Type of cartoon did make difference in level of aggression did make a difference it didn’t didn’t make a difference it did Mean approaches true population Shape approaches normality Variability goes down

58 3.5 12 3 25 100 4.0 84 percentile

Review Homework

r(18) = - 0.50 r(18) = - 0.40 r(18) = + 0.60 r(18) = - 0.811508835 500 400 300 200 100 500 400 300 200 100 500 400 300 200 100 Heating Cost Heating Cost Heating Cost 0 20 40 60 80 0 20 40 60 80 0 20 40 60 80 Average Temperature Insulation Age of Furnace r(18) = - 0.50 r(18) = - 0.40 r(18) = + 0.60 r(18) = - 0.811508835 r(18) = - 0.257101335 r(18) = + 0.536727562

r(18) = - 0.50 r(18) = - 0.40 r(18) = + 0.60 r(18) = - 0.811508835 500 400 300 200 100 500 400 300 200 100 500 400 300 200 100 Heating Cost Heating Cost Heating Cost 0 20 40 60 80 0 20 40 60 80 0 20 40 60 80 Average Temperature Insulation Age of Furnace r(18) = - 0.50 r(18) = - 0.40 r(18) = + 0.60 r(18) = - 0.811508835 r(18) = - 0.257101335 r(18) = + 0.536727562

+ 427.19 - 4.5827 -14.8308 + 6.1010 Y’ = 427.19 - 4.5827 x1 - 14.8308 x2 + 6.1010 x3

+ 427.19 - 4.5827 -14.8308 + 6.1010 Y’ = 427.19 - 4.5827 x1 - 14.8308 x2 + 6.1010 x3

+ 427.19 - 4.5827 -14.8308 + 6.1010 Y’ = 427.19 - 4.5827 x1 - 14.8308 x2 + 6.1010 x3

+ 427.19 - 4.5827 -14.8308 + 6.1010 Y’ = 427.19 - 4.5827 x1 - 14.8308 x2 + 6.1010 x3

+ 427.19 - 4.5827 -14.8308 + 6.1010 Y’ = 427.19 - 4.5827 x1 - 14.8308 x2 + 6.1010 x3

4.58 14.83 6.10 Y’ = 427.19 - 4.5827(30) -14.8308 (5) +6.1010 (10) Y’ = 427.19 - 137.481 - 74.154 + 61.010 = $ 276.56 = $ 276.56 Calculate the predicted heating cost using the new value for the age of the furnace Use the regression coefficient for the furnace ($6.10), to estimate the change

These differ by only one year but heating cost changed by $6.10 4.58 14.83 6.10 Y’ = 427.19 - 4.5827(30) -14.8308 (5) +6.1010 (10) Y’ = 427.19 - 137.481 - 74.154 + 61.010 = $ 276.56 Y’ = 427.19 - 4.5827(30) -14.8308 (5) +6.1010 (10) These differ by only one year but heating cost changed by $6.10 282.66 – 276.56 = 6.10 Y’ = 427.19 - 137.481 - 74.154 + 61.010 = $ 276.56 = $ 276.56 $ 276.56 Y’ = 427.19 - 4.5827(30) -14.8308 (5) +6.1010 (11) Y’ = 427.19 - 137.481 - 74.154 + 67.111 = $ 282.66 Calculate the predicted heating cost using the new value for the age of the furnace Use the regression coefficient for the furnace ($6.10), to estimate the change

4.0 3.0 2.0 1.0 4.0 3.0 2.0 1.0 4.0 3.0 2.0 1.0 GPA GPA GPA 0 1 2 3 4 0 200 300 400 500 600 0 200 300 400 500 600 High School GPA SAT (Verbal) SAT (Mathematical) r(7) = 0.50 r(7) = + 0.80 r(7) = + 0.80 r(7) = + 0.911444123 r(7) = + 0.616334867 r(7) = + 0.487295007

4.0 3.0 2.0 1.0 4.0 3.0 2.0 1.0 4.0 3.0 2.0 1.0 GPA GPA GPA 0 1 2 3 4 0 200 300 400 500 600 0 200 300 400 500 600 High School GPA SAT (Verbal) SAT (Mathematical) r(7) = 0.50 r(7) = + 0.80 r(7) = + 0.80 r(7) = + 0.911444123 r(7) = + 0.616334867 r(7) = + 0.487295007

4.0 3.0 2.0 1.0 4.0 3.0 2.0 1.0 4.0 3.0 2.0 1.0 GPA GPA GPA 0 1 2 3 4 0 200 300 400 500 600 0 200 300 400 500 600 High School GPA SAT (Verbal) SAT (Mathematical) r(7) = 0.50 r(7) = + 0.80 r(7) = + 0.80 r(7) = + 0.911444123 r(7) = + 0.616334867 r(7) = + 0.487295007

4.0 3.0 2.0 1.0 4.0 3.0 2.0 1.0 4.0 3.0 2.0 1.0 GPA GPA GPA 0 1 2 3 4 0 200 300 400 500 600 0 200 300 400 500 600 High School GPA SAT (Verbal) SAT (Mathematical) r(7) = 0.50 r(7) = + 0.80 r(7) = + 0.80 r(7) = + 0.911444123 r(7) = + 0.616334867 r(7) = + 0.487295007

- 0 .41107 No

- 0 .41107 No + 1.2013 Yes

- 0 .41107 No + 1.2013 Yes 0.0016 No

- 0 .41107 No + 1.2013 Yes 0.0016 No - 0 .0019 No

- 0 .41107 No + 1.2013 Yes 0.0016 No - 0 .0019 No High School GPA

- 0 .41107 No + 1.2013 Yes 0.0016 No - 0 .0019 No High School GPA Y’ = - 0 .41107 + 1.2013 x1 + 0 .0016 x2 - 0 .0019 x3

1.201 .0016 .0019 Y’ = - 0 .41107 + 1.2013 x1 + 0 .0016 x2 - 0 .0019 x3 Y’ = - 0 .411 + 1.2013 (2.8) + 0.0016 (430) - 0 .0019 (460) = 2.76 2.76

1.201 .0016 .0019 Y’ = - 0 .41107 + 1.2013 x1 + 0 .0016 x2 - 0 .0019 x3 Y’ = - 0 .411 + 1.2013 (3.8) + 0 .0016 (430) - 0 .0019 (460) = 3.96 3.96

1.201 .0016 .0019 2.76 3.96 3.96 - 2.76 = 1.2 Yes, use the regression coefficient for the HS GPA (1.2), to estimate the change

Today we will be reviewing for the test using clicker questions.

What is the null hypothesis of a correlation coefficient. a What is the null hypothesis of a correlation coefficient?  a. It is zero (nothing going on) b. It is less than zero c. It is more than zero d. It equals the computed sample correlation Correct

Let’s try one Winnie found an observed correlation coefficient of 0, what should she conclude? a. Reject the null hypothesis b. Do not reject the null hypothesis c. Not enough info is given Correct

coefficient of determination = r2 If the coefficient of determination is 0.80, what percent of variation is explained?  a. 20% b. 90% c. 64% d. 80%   Correct coefficient of determination = r2 What percent of variation is not explained?  a. 20% b. 90% c. 64% d. 80%   Correct

Which of the following represents a significant finding: a. p < 0.05 b. t(3) = 0.23; n.s. c. the observed t statistic is nearly zero d. we do not reject the null hypothesis Correct

Y’ = a + b1X 1 + b2X 2 + b3X 3 Correct In multiple regression what is the range of values for a coefficient of regression?  a.  0 to +1.0 b.  0 to -1.0 c.  -1.0 to +1.0 d.  Any number at all Correct Y’ = a + b1X 1 + b2X 2 + b3X 3

Correct If r = 1.00, which inference cannot be made? a. The dependent variable can be perfectly predicted by the independent variable b. This provides evidence that the dependent variable is caused by the independent variable c. All of the variation in the dependent variable can be accounted for by the independent variable d. Coefficient of determination is 100%.

Let’s try one In a regression analysis what do we call the variable used to predict the value of another variable?  a. Independent b. Dependent c. Correlation d. Determination Correct

  What can we conclude if the coefficient of determination is 0.94?  a.  r2 = 0.94 b. direction of relationship is positive c.  94% of total variation of one variable is explained by variation in the other variable. d.  Both A and C Correct

Which of the following statements regarding the coefficient of correlation is true?  a. It ranges from -1.0 to +1.0 b. It measures the strength of the relationship between two variables c. A value of 0.00 indicates two variables are not related d. All of these Correct

coefficient of correlation = r coefficient of determination = r2 What does a coefficient of correlation of 0.70 infer? (r = +0.70)  a. Almost no correlation because 0.70 is close to 1.0 b. 70% of the variation in one variable is explained by the other c. Coefficient of determination is 0.49 d. Coefficient of nondetermination is 0.30 Correct coefficient of correlation = r coefficient of determination = r2

The Pearson product-moment correlation coefficient, r, requires that variables are measured with:  a. an interval scale b. a ratio scale c. a nominal scale d. either A or B. Correct

  If r = 0.65, what does the coefficient of determination equal?  a. 0.194 b. 0.423 c. 0.577 d. 0.806 Correct

If the coefficient of correlation is 0 If the coefficient of correlation is 0.60, what percent of variation is not explained?  a. 20% b. 90% c. 64% d. 80%   Correct

If the coefficient of determination is 0 If the coefficient of determination is 0.20, what percent of variation is not explained?  a. 20% b. 90% c. 64% d. 80%   Correct

What is the measure that indicates how precise a prediction of Y is based on X or, conversely, how inaccurate the prediction might be?  a. Regression equation b. Slope of the line c. Standard error of estimate d. Least squares principle 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

Agnes compared the heights of the women’s gymnastics team and the scores they got. If she doubled the number of players measured, but ended up with the same correlation (r) what effect would that have on the results? Let’s try one a. the r is the same, so the conclusion would be the same b. the r is the same, but with more people, degrees of freedom (df) would go up and it would be harder to reject the null hypothesis. c. the r is the same, but with more people, degrees of freedom (df) would go up and it would be easier to reject the null hypothesis. Correct

Standard error of the estimate (line) Correct Which of the following is true about the standard error of estimate?  a. It is a measure of the accuracy of the prediction b. It is based on squared vertical deviations between Y and Y’ c. It cannot be negative d. All of these Correct Standard error of the estimate: a measure of the average amount of predictive error the average amount that Y’ scores differ from Y scores a mean of the lengths of the green lines

Standard error of the estimate (line) Correct If all the plots on a scatter diagram lie on a straight line, (perfect correlation) what is the standard error of estimate?  a. - 1 b. +1 c. 0 d. Infinity Correct Standard error of the estimate: a measure of the average amount of predictive error the average amount that Y’ scores differ from Y scores a mean of the lengths of the green lines

Let’s try one Scatterplot A Scatterplot B Scatterplot C Which of these correlations would be most likely to have the highest positive value for r? a. Scatterplot A b. Scatterplot B c. Scatterplot C d. Can not be determined from the information given Correct

Let’s try one Scatterplot A Scatterplot B Scatterplot C Which of the these scatterplots will have the smallest “y intercept”? a. Scatterplot A b. Scatterplot B c. Scatterplot C d. Can not be determined from the information given Correct

Let’s try one Scatterplot A Scatterplot B Scatterplot C Which of the these correlations would be most likely to represent the correlation between salary and expenses? a. Scatterplot A b. Scatterplot B c. Scatterplot C d. Can not be determined from the information given Correct

Let’s try one Which of the following correlations would allow you the most accurate predictions? a. r = + 0.01 b. r = - 0.10 c. r = + 0.40 d. r = - 0.65 Correct

Let’s try one After duplicate correlations have been discarded and trivial correlations have been ignored, there remain a. two correlations b. three correlations c. six correlations d. nine correlations Correct

Let’s try one Which of the following conclusions can not be made from the data in the matrix? a. There is a significant correlation between Science and Reading b. There is a significant correlation between Math and Reading c. There is a significant correlation between Math and Science Correct

What if we were looking to see if our stop-smoking program affects peoples‘ desire to smoke. What would null hypothesis be? a. Can’t know without knowing the dependent variable b. The program does not work c. The programs works d. Comparing the null and alternative hypothesis Correct

Correct Which of the following is a Type I error: a. We conclude that the program works when it fact it doesn’t b. We conclude that the program works when in fact it does c. We conclude that the program doesn’t work when in fact it does d. We conclude that the program doesn’t work when in fact it doesn’t

Let’s try one Harry, AJ and Willie were among six volunteers and were trying to draw straws to randomly pick one person to save the day. All six were equally likely to be picked. Each person had a 17% chance of being chosen. Which approach to probability is reflected here? a. Empirical b. Subjective c. Classical d. Conditional . correct

Let’s try one While in the Prancing Pony Tavern Frodo was given a note that listed the number of creatures found along the road. Help him calculate the likelihood of running into another Hobbit. a. .10 b. .20 c. .30 d. .40 Type of peoples Number seen on the road Dwarves 10 Elves 15 Hobbits 5 Men 20 correct

Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait. Which of the following is true? correct a. The null hypothesis is that there is no difference in the amount of shrimp caught b. The null hypothesis is that there is a difference in the amount of shrimp caught

Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait. A Type I Error would claim that … correct 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

Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait. He reported that there was a significant difference. Which of the following is true? a. p < 0.05 b. The observed t score was bigger than the critical score c. He can reject the null hypothesis d. All of the above correct

a. This is a one-tailed test because he made a specific prediction Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait. He reported that there was a significant difference. Which of the following is true? a. This is a one-tailed test because he made a specific prediction b. This is a two-tailed test because he made a specific prediction c. This is a one-tailed test because he made no specific prediction d. This is a two-tailed test because he made no specific prediction correct

b. one-sample t-test c. two-sample t-test d. one-sample z-test Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait. He reported that there was a significant difference. Which of the following best describes his study? a. correlation b. one-sample t-test c. two-sample t-test d. one-sample z-test correct

b. one-sample t-test c. two-sample t-test d. one-sample z-test Let’s try one Forrest wanted to know whether he caught more shrimp than is typical for all of the shrimp captains in the area. He compared the mean of his sample with the mean of the whole population of shrimp captains in the area. He does NOT know the standard deviation of the population but estimates it with his sample. Which of the following best describes his study? a. correlation b. one-sample t-test c. two-sample t-test d. one-sample z-test correct

d. smaller than the variance Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He calculated the mean and standard deviation for the amount of shrimp caught (in pounds). The standard deviation could never be ___ a. zero b. smaller than the mean c. a negative number d. smaller than the variance correct

a. standard deviation is for a population, variance is for samples Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He calculated the mean and standard deviation for the amount of shrimp caught (in pounds). He found that ___ a. standard deviation is for a population, variance is for samples b. standard deviation is for samples, variance is for a population c. standard deviation is the square root of variance d. standard deviation is the square of variance correct

a. amount of shrimp caught, which is a nominal level of measurement Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait The independent variable is ___ a. amount of shrimp caught, which is a nominal level of measurement b. amount of shrimp caught, which is a ratio level of measurement c. type of bait used, which is a nominal level of measurement d. type of bait used, which is a ratio level of measurement correct

a. amount of shrimp caught, which is a nominal level of measurement Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait The dependent variable is ___ a. amount of shrimp caught, which is a nominal level of measurement b. amount of shrimp caught, which is a ratio level of measurement c. type of bait used, which is a nominal level of measurement d. type of bait used, which is a ratio level of measurement correct

a. negatively skewed distribution and the mean is larger than the mode Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds). He created a distribution of the weights of the shrimp and found the following curve. Which of the following is true? This is a ____ correct a. negatively skewed distribution and the mean is larger than the mode b. negatively skewed distribution and the mean is smaller than the mode c. positively skewed distribution and the mean is larger than the mode d. positively skewed distribution and the mean is smaller than the mode

Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He calculated the mean and standard deviation for the amount of shrimp caught (in pounds). He found that the 50% percentile was identical to the a. mean b. median c. mode d. all of the above correct

a. continuous and qualitative b. continuous and quantitative Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait The independent variable is ___ a. continuous and qualitative b. continuous and quantitative c. discrete and qualitative d. discrete and quantitative correct

a. continuous and qualitative b. continuous and quantitative Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait The dependent variable is ___ a. continuous and qualitative b. continuous and quantitative c. discrete and qualitative d. discrete and quantitative correct

c. Temperature (Fahrenheit) d. All of the above Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait Which of the following is an interval level of measurement? a. Forrest’s hat size b. Forrest’s GPA c. Temperature (Fahrenheit) d. All of the above correct

a. amount of shrimp caught b. type of bait used Let’s try one Forrest wanted to know which type of shrimp bait will result in more shrimp being caught. He compared the amount of shrimp caught (in pounds) when he used the two different types of bait The research question is ___ a. amount of shrimp caught b. type of bait used c. whether the type of bait affected the amount of shrimp caught d. all of the above correct

Let’s try one Forrest looked at the correlation between the amount of shrimp caught (in pounds) and the amount of bait used. He found a strong positive correlation. Which of the following would best depict this relationship a. b. c. correct

a. Point estimate ± Standard error b. Point estimate ± Margin of error Let’s try one Forrest wanted to create a confidence interval that predicts the average amount of shrimp that is caught. What is the most typical form of a calculated confidence interval? a. Point estimate ± Standard error b. Point estimate ± Margin of error c. Population parameter ± Standard error d. Population parameter ± Margin of error correct (z)(sem) = margin of error (t)(sem) = margin of error Point Estimate = mean

a. becomes more negatively skewed b. becomes more positively skewed Let’s try one The central limit theorem states that, for any distribution, as n gets larger, the shape of the sampling distribution of the sample mean _______. a. becomes more negatively skewed b. becomes more positively skewed c. becomes closer to a normal distribution d. becomes closer to the standard deviation correct

Let’s try one The central limit theorem states that, for any distribution, as n gets larger, the variability of the sampling distribution of the sample means _______. a. gets smaller b. gets larger c. stays the same correct

a. gets smaller and it becomes easier to reject the null Let’s try one The central limit theorem states that, for any distribution, as n gets larger, the variability of the sampling distribution of the sample means _______. a. gets smaller and it becomes easier to reject the null b. gets smaller and it becomes harder to reject the null c. gets larger and it becomes easier to reject the null d. gets larger and it becomes harder to reject the null correct

a. gets smaller and the confidence gets wider Let’s try one The central limit theorem states that, for any distribution, as n gets larger, the variability of the sampling distribution of the sample means _______. a. gets smaller and the confidence gets wider b. gets smaller and the confidence gets narrower c. gets larger and the confidence gets wider d. gets larger and the confidence gets narrower correct

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

Let’s try one If Alberta reported that t(198) = 2.38; p < 0.05 when he compared the race times of equal numbers of male and female jockeys for race horses. We know that a. She had 100 female jockeys and 100 male jockeys and there was no significant difference between the two groups b. She had 100 female jockeys and 100 male jockeys and there was a significant difference between the two groups c. 99 female jockeys and 99 male jockeys and there was no significant difference between the two groups d. 99 female jockeys and 99 male jockeys and there was no significant difference between the two groups 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 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 variance would get bigger and the confidence interval would get wider b. the variance would get bigger and the confidence interval would get narrower c. the variance would get smaller and the confidence interval would get wider d. the variance would get smaller and the confidence interval would get narrower 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

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 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’ 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

correct A survey was conducted to see whether men or women superintendents make more money. The independent variable is a. nominal level of measurement b. ordinal level of measurement c. interval level of measurement d. ratio level of measurement correct

correct A survey was conducted to see whether men or women superintendents make more money. The dependent variable is a. nominal level of measurement b. ordinal level of measurement c. interval level of measurement d. ratio level of measurement correct

correct A survey was conducted to see whether men or women superintendents make more money. The dependent variable is a. continuous and qualitative b. continuous and quantitative c. discrete and qualitative d. discrete and quantitative correct

correct A survey was conducted to see whether men or women superintendents make more money. This is a a. quasi, between subject design b. quasi, within subject design c. true, between subject design d. true, within subject design correct

correct A survey was conducted to see whether men or women superintendents make more money. This is a a. one-tailed test b. two-tailed test c. three-tailed test d. not enough information correct

correct A survey was conducted to see whether men or women superintendents make more money. The null hypothesis is a. men make more money b. women make more money c. no difference between amount of money made d. there is a difference between the amount of money made correct

correct A survey was conducted to see whether men or women superintendents make more money. If the null hypothesis was rejected we will conclude that a. men make more money b. women make more money no difference between amount of money made d. there is a difference between the amount of money made correct

correct A survey was conducted to see whether men or women superintendents make more money. A Type I error would be a. claiming men make more money, when they don’t b. claiming women make more money, when they don’t claiming no difference between amount of money made, when there is a difference d. claiming there is a difference between the amount of money made, when there is no difference correct

correct A survey was conducted to see whether men or women superintendents make more money. A Type II error would be a. claiming men make more money, when they don’t b. claiming women make more money, when they don’t claiming no difference between amount of money made, when there is a difference d. claiming there is a difference between the amount of money made, when there is no difference correct

correct A t-test was conducted, there were ___ men in the study and ___ women. a. 18; 21 b. 21; 18 c. 19; 19 d. 38; 38 correct

Test yourself – Just for fun A t-test was conducted, which of the following best describes the results: a. t(21) = 2.02; p < 0.05 b. t(21) = 2.02; n.s. c. t(37) = 5.0; p < 0.05 d. t(37) = 5.0; n.s correct

A t-test was conducted, with a two tail test was there a significant difference? a. No, because 5.0 is not bigger than 6.89 b. Yes, because 5.0 is bigger than 1.68. c. Yes, because 5.0 is bigger than 1.37 d. Yes, because 5.0 is bigger than 2.02 correct

correct Which is true a. p < 0.05 b. p < 0.01 c. p < 0.001 d. All of the above correct

Note the change in the problem A survey was conducted to see whether women superintendents make more money than men. This is a a. one-tailed test b. two-tailed test c. three-tailed test d. not enough information correct Note the change in the problem

A survey was conducted to see whether women superintendents make more money than men. A t-test was conducted, which of the following best describes the results: Note the results were in the unpredicted direction a. reject the null b. do not reject the null c. not enough information correct

A survey was conducted to see whether women superintendents make more money than men. A t-test was conducted, which of the following best describes the results: Note the results were in the unpredicted direction a. t(21) = 2.02; p < 0.05 b. t(21) = 2.02; n.s. c. t(37) = 5.0; p < 0.05 d. t(37) = 5.0; n.s correct

Let’s try one What is the critical t score for a 99% confidence interval of the population mean based on a sample of 25 observations? A. 2.492 B. 2.576 C. 2.787 D. 2.797

Let’s try one What is the critical t score for a 95% confidence interval of the population mean based on a sample of 15 observations? A. 1.761 B. 1.960 C. 2.131 D. 2.145

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. 1.859 c. 2.306 d. .004 e. .008 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 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 117

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

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

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

Thank you! See you next time!!