active learning lecture slides for use with classroom response systems association: contingency,...

Active Learning Lecture Slides For use with Classroom Response Systems

Association: Contingency, Correlation, and

Regression

Copyright © 2013 Pearson Education, Inc.

3.1 Below is a contingency table of the results of two

questions asked during the 2006 GSS. Participants

were asked if gun control should be stricter after the

9/11/01 tragedy and about their political party

affiliation. Find the conditional proportion of

Republicans that think that gun control laws should be

stricter.

a) 363 / 1215

b) 363 / 1012

c) 363 / 467

d) 1012 / 1215

e) 467 / 1215

Should be

stricter

Should

be less

strict

Total

Democrat 454 62 516

Independent 195 37 232

Republican 363 104 467

Total 1012 203 1215


3.5 A psychologist believes that people who have a

religious belief system are happier. She asks 10

people each of the Jewish, Christian, Islamic, Hindu

and Buddhist religions as well as 10 people who claim

no religion to rate their happiness on a 5 point scale.

Which more naturally is the response variable and the

explanatory variable?

a) Explanatory variable: happiness rating

Response variable: religion

b) Explanatory variable: religion

Response variable: happiness rating

c) Cannot be determined


3.6 What type of graphic would you use to

explore the association between two quantitative

variables?

a) Contingency Table

b) Side-by-Side Boxplots

c) Scatterplots

d) All of the above


3.7 The scatterplot below shows a graph of median

family incomes per state as determined by the US

Census for 1969 versus 1989. In general, what can be

said about the straight line association between the

variables?

a) Strong, negative

b) Strong, positive

c) Weak, negative

d) Weak, positive

http://www.census.gov/hhes/www/income/histinc/state/state2.html


3.8 Which of the following properties is NOT a

property of correlation (r)?

a) It is unitless.

b) It ranges from –1 to 1.

c) It measures the strength of any type of

relationship between x and y.

d) If r = 0.9, the data exhibits a positive linear

relationship.

e) It is not resistant to outliers.


3.9 What value of “r” below best describes the

scatterplot below?

a) 0.9

b) -0.9

c) 0.3

d) -0.3

e) 0


3.10 What value of “r” below would you expect if

you were comparing the number of hours that

students spend studying versus their GPA?

a) 0.99

b) 0.70

c) 0.00

d) -0.70


3.11 A least squares regression equation was

created from last year’s students data to predict

Exam 3 scores based on Exam 1 scores. The

equation was:

a) 69.70

b) 79.89

c) 85.53

d) 89.33

e) 90.53

xy 4845.057.50ˆ

Predict the score on Exam 3 for a student that scored an 80 on Exam 1.


3.12 In northern cities roads are salted to keep ice from freezing

on the roadways between 0 and -9.5° C. Suppose that a small

city was trying to determine what was the average amount of salt

(in tons) needed per night at certain temperatures. They found

the following LSR equation: xy 500,2000,20ˆ

Interpret the y-intercept.

a) 2,500 tons is the average decrease in the amount of salt needed for a 1 degree increase in temperature.

b) Do not interpret. There is no data around x= 0° C.

c) 20,000 tons is the predicted amount of salt needed when the temperature is 0° C.

d) 2,500 tons is the predicted amount of salt needed when the temperatures is 0° C.


3.13 In northern cities roads are salted to keep ice from freezing on the roadways between 0 and -9.5° C. Suppose that a small city was trying to determine what was the average amount of salt (in tons) needed per night at certain temperatures. They found the following LSR equation:

xy 500,2000,20ˆ

Interpret the slope.

a) 2,500 tons is the average decrease in the amount of salt

needed for a 1 degree increase in temperature.

b) 2,500 tons is the average increase in the amount of salt

needed for a 1 degree increase in temperature.

c) 20,000 is the average increase in the amount of salt needed

for a 1 degree increase in temperature.


3.15 A least squares regression equation was

created from last year’s students data to predict

Exam 3 scores based on Exam 1 scores. The

equation was: xy 4845.057.50ˆ

Suppose that a student made a 60 on Exam 1 and an 80 on Exam 3. Find the residual.

a) 0.36

b) 0.54

c) -0.36

d) -0.54

e) Cannot be determined


3.17 The GSS survey asked married men from 1974

to 2006 how happy they were in their marriage.

According to this formula, in 2050 only 51.5% of

married men will be very happy. What type of error

has been made here?

xy 174.02.408ˆ

a) Simpson’s Paradox

b) Interpolation

c) Extrapolation

d) Confounding

e) No error has been made


3.18 From 1980 to 2002, Americans were asked if they

would feel safe traveling on a commercial airplane. A plot of

the year versus the percentage that would feel safe is shown

below. Comment on what is happening in the plot.

a) Evidence of extrapolation

b) Evidence of a regression outlier

c) Evidence of confounding

d) Evidence of nonresponse


3.19 True or False: If two variables have a

correlation equal to 0.99, x must cause y.

a) True

b) False

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