Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Spring 2016 Room 150 Harvill.

Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Spring 2016 Room 150 Harvill Building 9:00 - 9:50 Mondays, Wednesdays & Fridays

By the end of lecture today 3/2/16 Confidence Intervals Review for Exam 2

Homework No new homework – just study for Exam 2

Before next exam (March 4 th ) Please read chapters 1 - 8 in OpenStax textbook Please read Chapters 10, 11, 12 and 14 in Plous Chapter 10: The Representativeness Heuristic Chapter 11: The Availability Heuristic Chapter 12: Probability and Risk Chapter 14: The Perception of Randomness Schedule of readings

Everyone will want to be enrolled in one of the lab sessions Labs continue With Exam 2 Prep

Confidence interval uses SEM

Upper boundary raw score x = mean + (z)(standard deviation) x = 55 + (+ 2.58)(10) x = 80.8 Lower boundary raw score x = mean + (z)(standard deviation) x = 55 + (- 2.58)(10) x = 29.2 29.2 80.8 29.2 80.8

Upper boundary raw score x = mean + (z)(standard error mean) x = 55 + (+ 2.58)(1.42) x = 58.7 Lower boundary raw score x = mean + (z)(standard error mean) x = 55 + (- 2.58)(1.42) x = 51.3 29.2 80.8 51.3 58.7 10 49 1.42 51.3 58.7

29.2 80.8 58.7 8.02 8.6 9.18 7.8 8.6 9.4 51.3 10.2 29.8 23.1 16.9 4.09 13.11 9.18 8.02 2.67 14.5 9.4 7.8

Let’s try one

Alia is looking at a normal distribution and wants to know what proportion of the distribution that falls between 1 and -1 standard deviations from the mean. What is the correct proportion? a..3413 b..6826 c..9544 d..9970 Let’s try one Correct Answer

This will be so helpful now that we know these by heart 1 sd above and below mean 68% 2 sd above and below mean 95% 3 sd above and below mean 99.7%

When Stephan created this normal distribution, what did he plot on the “y” axis? (Remember to draw a picture.) a. memory test performance b. age of preschoolers c. frequency d. products advertised during their shows Let’s try one Correct Answer

Variability and means 38 40 44 48 52 56 58 40 44 48 52 56 Remember, there is an implied axis measuring frequency f f

“If random samples of a fixed N are drawn from any population, as N becomes larger, the distribution of sample means approaches normality, with the overall mean approaching the theoretical population mean.” This is an example of? a. law of large numbers b. hypothesis test c. central limit theorem d. multiplication law for independent events Let’s try one Correct Answer

Proposition 1: If sample size ( n ) is large enough (e.g. 100) The mean of the sampling distribution will approach the mean of the population Central Limit Theorem Proposition 2: If sample size ( n ) is large enough (e.g. 100) The sampling distribution of means will be approximately normal, regardless of the shape of the population XXXXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXX XXXXXX XXXX XXXX X X XXXXXXXXXX XXXXXXXXXX X XXXXXXXXXX Proposition 3: The standard deviation of the sampling distribution equals the standard deviation of the population divided by the square root of the sample size. As n increases SEM decreases. As n ↑ x will approach µ As n ↑ curve will approach normal shape As n ↑ curve variability gets smaller

Law of large numbers: As the number of measurements increases the data becomes more stable and a better approximation of the true (theoretical) probability. Larger sample sizes tend to be associated with stability. As the number of observations ( n ) increases or the number of times the experiment is performed, the estimate will become more accurate.

Elle Woods is applying to law school and hopes to attend Harvard Law. She took the LSAT (Law School Admission Test). Which of the following percentile ranks would represent the best score on this test? a. 2 percentile b. 45 percentile c. 75 percentile d. 98 percentile Let’s try one Correct Answer

When estimating the population mean (µ) using a “point estimation”, one should use a. standard deviation b. standard error of the mean of the sample c. the mean of the sample d. the population mean (µ) cannot be estimated using the “point estimation” Let’s try one Correct Answer

Which of the following is inconsistent with the Central Limit Theorem: If random samples of a fixed N are drawn from any population as N becomes larger, a. the distribution of sample means approaches normality (regardless of the shape of the population distribution) b. the overall mean approaches the theoretical population mean c. The standard deviation of the sampling distribution equals the standard deviation of the population divided by the square root of the sample size. d. the dispersion of scores also becomes larger Let’s try one Correct Answer

Imagine that a Fatima takes a random sample from the population, and calculates the mean of that sample. Then, the procedure is repeated with a new sample (of the same size) generating a new mean, and then repeated again several times. If the Fatima drew a graph that represented the frequency of all of these means, the graph would be called a a. regularity distribution of central limits b. sampling distribution of sample means c. mean distribution of samples d. variance distribution of deviations Let’s try one Correct Answer

Sampling distribution: is a theoretical probability distribution of the possible values of some sample statistic that would occur if we were to draw an infinite number of same-sized samples from a population XXXXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXX XXXXXX XXXX XXXX X X XXXXXXXXXX XXXXXXXXXX X XXXXXXXXXX 2 nd sample 23 rd sample Sampling distributions sample means theoretical distribution we are plotting means of samples Frequency distributions of individual scores derived empirically we are plotting raw data this is a single sample Melvin Eugene

According to the Central Limit Theorem, for very large sample sizes, the mean of the sampling distribution of means a. underestimates the population mean b. equals the population mean c. overestimates the population mean d. has no relationship with the population mean Let’s try one Correct Answer

According to the Central Limit Theorem, for very large sample sizes, the distribution of sample means from a skewed population is a. skewed b. approximately normal c. binomial d. bimodal Let’s try one Correct Answer

According to the Central Limit Theorem as sample sizes get larger, the variability of the sampling distribution of means _______. a. becomes more positively skewed b. becomes smaller c. remains the same d. becomes larger Let’s try one Correct Answer

Which of the following is not one of the three propositions of the Central Limit Theorem a. If sample size (n) is large enough, the mean of the sampling distribution will approach the mean of the population b. If sample size (n) is large enough, the sampling distribution of means will be approach normality c. If sample size (n) is large enough, the standard deviation of the sampling distribution equals the standard deviation of the population plus the square root of the sample size. d. As n increases SEM decreases Let’s try one Correct Answer

Fred was examining his company’s historical real estate data in attempt to predict what percentage of households built pools after buying a property without one. He counted all of the households that sold in the past couple years, and found that 60% of households actually built pools after buying houses without one. This is an example of: a. classic probability b. subjective probability c. empirical probability d. conditional probability Let’s try one Correct Answer

What is probability 1. Empirical probability: relative frequency approach Number of observed outcomes Number of observations Probability of hitting the corvette Number of carts that hit corvette Number of carts rolled 182 200 91% chance of hitting a corvette =.91

2. Classic probability: a priori probabilities based on logic rather than on data or experience. We assume we know the entire sample space as a collection of equally likely outcomes (deductive rather than inductive). Number of outcomes of specific event Number of all possible events In throwing a die what is the probability of getting a “2” Number of sides with a 2 Number of sides In tossing a coin what is probability of getting a tail Number of sides with a 1 Number of sides 1 2 50% chance of getting a tail 1 6 16% chance of getting a two = =

3. Subjective probability: based on someone’s personal judgment (often an expert), and often used when empirical and classic approaches are not available. There is a 50% chance that AT&T will merge with Cingular Bob says he is 90% sure he could swim across the river

There are 60 students in Kaisa’s physics class. The grades on the first midterm followed a normal distribution. What percent of the students were not within two standard deviations of the mean? a. 2.5% b. 5% c. 50% d. 95% Let’s try one Correct Answer

Louisa is excited that she scored 2.5 standard deviations above the mean on her chemistry test. The average was 50, and the standard deviation was 10. What grade did she receive? a. 75 b. 85 c. 95 d. 100 Let’s try one Correct Answer

Arthur knows that the probability of drawing the ace of spades from a standard deck of 52 is.01923, even though he has never actually tried it himself. What kind of probability is this? a. classic probability b. subjective probability c. empirical probability d. conditional probability Let’s try one Correct Answer

What is probability 1. Empirical probability: relative frequency approach Number of observed outcomes Number of observations Probability of hitting the corvette Number of carts that hit corvette Number of carts rolled 182 200 91% chance of hitting a corvette =.91

2. Classic probability: a priori probabilities based on logic rather than on data or experience. We assume we know the entire sample space as a collection of equally likely outcomes (deductive rather than inductive). Number of outcomes of specific event Number of all possible events In throwing a die what is the probability of getting a “2” Number of sides with a 2 Number of sides In tossing a coin what is probability of getting a tail Number of sides with a 1 Number of sides 1 2 50% chance of getting a tail 1 6 16% chance of getting a two = =

3. Subjective probability: based on someone’s personal judgment (often an expert), and often used when empirical and classic approaches are not available. There is a 50% chance that AT&T will merge with Cingular Bob says he is 90% sure he could swim across the river

Afra was interested in whether caffeine affects time to complete a cross-word puzzle, so she randomly assigned people to two groups. One group drank caffeine and the other group did not. She then timed them to see how quickly they could complete a crossword puzzle. This is an example of a a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA Let’s try one Correct Answer

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 Let’s try one Correct Answer

Stephan is researching the television-watching behavior of preschoolers. He gave them a memory test for products advertised during their favorite shows. He used these test results to create a normal distribution. This distribution had a mean of 30 and a standard deviation of 2. Find the raw score associated with the 13th percentile. (Remember to draw a picture.) a. 27.74 b. 29.26 c. 29.34 d. 32.26 Let’s try one Correct Answer

13 th percentile Go to table.3700 nearest z = 1.13 x = mean + z σ = 30 + (-1.13)(2) = 27.74

Taylor is attending a conference about social networking, and the people’s ages in the room have a mean of 26 and a standard deviation of 3. What proportion of people’s ages were between 20 and 32? (Remember to draw a picture.) a..3413 b..6826 c..9544 d..9970 Let’s try one Correct Answer

A distribution has a mean of 50 and a standard deviation of 10. Find the raw score associated with the 77th percentile. (Hint: it may be helpful to draw a picture) a..74 b. 42.6 c. 57.4 d. 57.7 Let’s try one Correct Answer

77 th percentile Go to table.2700 nearest z =.74 x = mean + z σ = 30 + (.74)(2) = 31.48 x = mean + z σ = 50 + (.74)(10) = 57.4 Correct Answer for test

A distribution has a mean of 50 and a standard deviation of 10. Find the raw score associated with the 33rd percentile. (Hint: it may be helpful to draw a picture) a..44 b. 40.5 c. 45.6 d. 54.4 Let’s try one Correct Answer

33 th percentile Go to table.1700 nearest z = -.44 x = mean + z σ = 50 + (-.44)(10) = 45.6

A distribution has a mean of 50 and a standard deviation of 10. Find the area under the curve associated with a score of 35 and above. (Hint: it may be helpful to draw a picture) a..0668 b. 1.5 c..9332 d..4332 Let’s try one Correct Answer Notice only one is bigger than.50

z = 35-50 10 z = 1.5 Go to table.4332 A distribution has a mean of 50 and a standard deviation of 10. Find the area under the curve associated with a score of 35 and above. (Hint: it may be helpful to draw a picture)

Spud Webb was an NBA basketball player who won the annual NBA “slam dunk” contest despite being one of the shortest NBA players of all time. He is 67” tall (5’7”). If we assume that the average height of NBA players is 80” (6’8”) with a standard deviation of 4”, we can calculate the z-score for Mr. Webb to be -3.5. This z-score would be classified as which of the following: a. not an unusual score b. an unusual score c. an outlier d. an extreme outlier Let’s try one Correct Answer

If score is within 2 standard deviations (z < 2) “not unusual score” If score is beyond 2 standard deviations (z ≥ 2) “is unusual score” If score is beyond 3 standard deviations (z ≥ 3) “is an outlier” If score is beyond 4 standard deviations (z ≥ 4) “is an extreme outlier”

Let’s try one Albert compared the time required to finish the race for 20 female jockeys and 20 male jockeys riding 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

Let’s try one Albert compared the time required to finish the race for 20 female jockeys and 20 male jockeys riding race horses. He wanted to know who averaged faster rides. The independent variable is a(n) _____ a. Nominal level of measurement b. Ordinal level of measurement c. Interval level of measurement d. Ratio level of measurement

Let’s try one Albert compared the time required to finish the race for 20 female jockeys and 20 male jockeys riding race horses. He wanted to know who averaged faster rides. The dependent variable is a(n) _____ a. Nominal level of measurement b. Ordinal level of measurement c. Interval level of measurement d. Ratio level of measurement

Let’s try one Albert compared the time required to finish the race for 20 female jockeys and 20 male jockeys riding race horses. He wanted to know who averaged faster rides. The independent variable is a(n) _____ a. Discrete b. Continuous

Let’s try one Albert compared the time required to finish the race for 20 female jockeys and 20 male jockeys riding race horses. He wanted to know who averaged faster rides. The dependent variable is a(n) _____ a. Discrete b. Continuous

Let’s try one Albert compared the time required to finish the race for 20 female jockeys and 20 male jockeys riding 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 c. This is a true, between participant design d. This is a true, within participant design

Let’s try one Albert compared the time required to finish the race for 20 female jockeys and 20 male jockeys riding race horses. He wanted to know who averaged faster rides. Which of the following is true? a. This is t-test b. This is an ANOVA c. This is a correlational design d. This is a chi square

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

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

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

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

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

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

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. between participant design b. within participant design c. mixed participant design

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. quasi experimental design b. true experimental design c. mixed participant design quasi

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

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

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

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 Let’s try one Relationship between GPA and Starting salary GPA Starting Salary correlation What type of analysis is this?

An automotive firm tested whether driving styles can affect gas efficiency in their cars. They observed 100 drivers and found there were four general driving styles. They recruited a sample of 100 drivers all of whom drove with one of these 4 driving styles. Then they asked all 100 drivers to use the same model car for a month and recorded their gas mileage. Then they compared the mean mpg for each driving style. This is an example of a _____. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA This is an example of a a. between participant design b. within participant design c. mixed participant design Let’s try another one This is an example of a a. true experimental design b. quasi-experimental design c. mixed design Let’s try another one Quasi-experiment Between One-way ANOVA What type of analysis is this?

Let’s try one Judy is running an experiment in which she wants to see whether a reward program will improve the number of sales in her retail shops. In her experiment she rewarded the employees in her Los Angeles stores with bonuses and fun prizes whenever they sold more than 5 items to any one customer. However, the employees in Houston were treated like they always have been treated and were not given any rewards for those 2 months. Judy then compared the number of items sold by each employee in the Los Angeles (rewarded) versus Houston (not rewarded) stores. In this study, a _____________ design was used. a. between-participant, true experimental b. between-participant, quasi experimental c. within-participant, true experimental d. within-participant, quasi experimental

Let’s try one Judy is running an experiment in which she wants to see whether a reward program will improve the number of sales in her retail shops. (As described in previous question). She wants to use her findings with these two samples to make generalizations about the population, specifically whether rewarding employees will affect sales to all of her stores. She wants to generalize from her samples to a population, this is called a. random assignment b. stratified sampling c. random sampling d. inferential statistics

Let’s try one Naomi is interested in surveying mothers of newborn infants, so she uses the following sampling technique. She found a new mom and asked her to identify other mothers of infants as potential research participants. Then asked those women to identify other potential participants, and continued this process until she found a suitable sample. What is this sampling technique called? a. Snowball sampling b. Systematic sampling c. Convenience sampling d. Judgment sampling

Let’s try one Steve who teaches in the Economics Department wants to use a simple random sample of students to measure average income. Which technique would work best to create a simple random sample? a. Choosing volunteers from her introductory economics class to participate b. Listing the individuals by major and choosing a proportion from within each major at random c. Numbering all the students at the university and then using a random number table pick cases from the sampling frame. d. Randomly selecting different universities, and then sampling everyone within the school.

Let’s try one Marcella wanted to know about the educational background of the employees of the University of Arizona. She was able to get a list of all of the employees, and then she asked every employee how far they got in school. Which of the following best describes this situation? a. census b. stratified sample c. systematic sample d. quasi-experimental study

Let’s try one Mr. Chu who runs a national company, wants to know how his Information Technology (IT) employees from the West Coast compare to his IT employees on the East Coast. He asks each office to report the average number of sick days each employee used in the previous 6 months, and then compared the number of sick days reported for the West Coast and East Coast employees. His methodology would best be described as: a. time-series comparison b. cross-sectional comparison c. true experimental comparison d. both a and b

Let’s try one A researcher wrote the following item stem for a five point rating scale. "Don't you agree that the University needs a football team.” What is the problem with this item? a. It uses unfamiliar language. b. It uses double negatives. c. It is a double-barreled question. d. It is a "leading" question.

Let’s try one A researcher wrote the following item for a survey on school financing (they were to agree or disagree with the statement), "Parents should support the schools and taxes should be increased." What is the problem with this item? a. It uses unfamiliar language. b. It uses double negatives. c. It is a double-barreled question. d. It is a "leading" item.

Let’s try one When several items on a questionnaire are rated on a five point scale, and then the responses to all of the questions are added up for a total score (like in a miniquiz), it is called a: a. Checklist b. Likert scale c. Open-ended scale d. Ranking

Let’s try one Which of the following is a measurement of a construct (and not just the construct itself) a. sadness b. customer satisfaction c. laughing d. love

What if we were looking to see if our new management program provides different results in employee happiness than the old program. What is the independent variable? a. The employees’ happiness b. Whether the new program works better c. The type of management program (new vs old) d. Comparing the null and alternative hypothesis How many levels of the IV are there?

What if we were looking to see if our new management program provides different results in employee happiness than the old program. What is the dependent variable? a. The employees’ happiness b. Whether the new program works better c. The type of management program (new vs old) d. Comparing the null and alternative hypothesis

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 What type of analysis is this? Let’s try one This is an example of a a. between participant design b. within participant design c. mixed participant design Let’s try another one t-test Between

Marietta is a manager of a movie theater. She wanted to know whether there is a difference in concession sales for people of all ages. She simply measured their age and how much they spent on treats. This is an example of a _____. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA What type of analysis is this? Let’s try one Correlation

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 Let’s try one Matinee Evening Concession purchase a. Movie Time Concession b. Movie Times Concession purchase d. c. Concession purchase Movie Times Two means What type of analysis is this? t-test

Gabriella is a manager of a movie theater. She wanted to know whether there is a difference in concession sales between teenage couples and middle-aged couples. She also wanted to know whether time of day makes a difference (matinee versus evening shows). She gathered the data for a sample of 25 purchases from each pairing. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA Let’s try one What are the two IV? What are the levels of each? Two-way ANOVA What type of analysis is this?

Gabriella is a manager of a movie theater. She wanted to know whether there is a difference in concession sales between teenage couples and middle-aged couples. She also wanted to know whether time of day makes a difference (matinee versus evening shows). She gathered the means for a sample of 25 purchases from each pairing. Let’s try one Matinee Older couples Evening Teenagers Concession purchase a. Movie Time Old / young b. c. Concession purchase Matinee Older couples Evening Teenagers Evening Older couples Movie Times Concession purchase d. Older couples Teenagers Matinee Evening Four means What type of analysis is this?

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 Let’s try one This is an example of a a. between participant design b. within participant design c. mixed participant design Let’s try another one t-test What type of analysis is this? Within

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 Let’s try one Relationship between GPA and Starting salary GPA Starting Salary correlation What type of analysis is this?

An automotive firm tested whether driving styles can affect gas efficiency in their cars. They observed 100 drivers and found there were four general driving styles. They recruited a sample of 100 drivers all of whom drove with one of these 4 driving styles. Then they asked all 100 drivers to use the same model car for a month and recorded their gas mileage. Then they compared the mean mpg for each driving style. This is an example of a _____. a. correlation b. t-test c. one-way ANOVA d. two-way ANOVA Let’s try one This is an example of a a. between participant design b. within participant design c. mixed participant design Let’s try another one This is an example of a a. true experimental design b. quasi-experimental design c. mixed design Let’s try another one Quasi-experiment Between One-way ANOVA What type of analysis is this?

Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Spring 2016 Room 150 Harvill.

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Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Spring 2016 Room 150 Harvill.

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Presentation on theme: "Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Spring 2016 Room 150 Harvill."— Presentation transcript:

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