1. Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2018 Room 150 Harvill Building 10: :50 Mondays, Wednesdays & Fridays.
Welcome
10/10/18

2. Alyson Lecturer’s desk Chris Flo Jun Trey Projection Booth Screen
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Projection Booth
Left handed desk
Harvill 150
renumbered

3. ..
The
Green
Sheets

4. Study Guide posted Schedule of readings
Before next exam (October 12th)
Please read chapters 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

5. Just study for the Exam on Friday
No homework
Just study for the Exam on Friday

6. Lab sessions
Labs Prep
for Exam 2

7. Hand out z tables

8. z table Formula Normal distribution Raw scores z-scores probabilities
Have z
Find raw score Z
Scores
Have z
Find area
z table
Formula
Have area
Find z
Area &
Probability
Have raw score
Find z
Raw Scores

9. 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
correct .
Let’s try one

10. 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
Correct
Answer
Let’s try one

11. 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
b c d
Correct
Answer
Let’s try one

12. 13th percentile
Go to
table
nearest z = 1.13
.3700
x = mean + z σ = 30 + (-1.13)(2) = 27.74
.37
.50
.13 24 ? 26
27.74 30 32 34 36

13. Let’s try one Correct Answer
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 b c d
Correct
Answer
Let’s try one

14. Homework Worksheet: Problem 2
2 sd
2 sd
.9544 26 28 30 32 34

15. 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 b c d
Correct
Answer
Let’s try one

16. 77th percentile
Go to
table
nearest z = .74
.2700
x = mean + z σ = 50 + (.74)(10) = 57.4
.7700
.27
.5000 50 ?
57.4

17. 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 33rd percentile. (Hint: it may be helpful to draw a picture)
a b c d
Correct
Answer
Let’s try one

18. 33th percentile
Go to
table
nearest z = -.44
.1700
x = mean + z σ = 50 + (-.44)(10) = 45.6
.17
.50
.33
45.6 ? 50

19. Notice only one is bigger than .50
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
b c d
Correct Answer
Notice only one is bigger than .50
Let’s try one

20. 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)
35-50
Go to
table
z =
z = 1.5
.4332 10
.9332
.4332
.5000 35 50 36

21. Let’s try one Correct Answer
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 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
Correct
Answer
Let’s try one

22. 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”

24. 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?
correct
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

25. 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
correct

26. 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
correct

27. 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) _____
correct
a. Discrete b. Continuous

28. 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?
correct
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

29. 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?
correct
a. This is t-test b. This is an ANOVA c. This is a correlational design d. This is a chi square .

30. 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.

31. 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

32. 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

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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

39. 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

40. 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

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

42. 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
One-way ANOVA
Let’s try another one
Between
Let’s try another one
Quasi-experiment
This is an example of a
a. between participant design
b. within participant design
c. mixed participant design
This is an example of a
a. true experimental design
b. quasi-experimental design
c. mixed design

43. 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

44. 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

45. 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

46. 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.

47. 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

48. 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

49. 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

50. 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

51. 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 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

52. 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

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

54. What type of analysis is this?
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
Correlation
Let’s try one

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

56. 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 data for a sample of 25 purchases from each pairing.
a. correlation
b. t-test
c. one-way ANOVA
d. two-way ANOVA
Two-way ANOVA
What are the two IV?
What are the levels of each?
Let’s try one

57. 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.
Matinee
Older couples
Evening
Teenagers
Concession purchase a. c.
Concession purchase
Matinee
Older couples
Evening
Teenagers
Movie Times
Concession purchase d.
Older couples
Teenagers
Movie Time
Old / young b.
Matinee
Evening
Four means
Let’s try one

58. 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
t-test
Let’s try another one
Let’s try one
This is an example of a
a. between participant design
b. within participant design
c. mixed participant design
Within

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

60. 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
One-way ANOVA
Let’s try another one
Between
Let’s try another one
Quasi-experiment
This is an example of a
a. between participant design
b. within participant design
c. mixed participant design
This is an example of a
a. true experimental design
b. quasi-experimental design
c. mixed design

61. Thank you!
See you next time!!