Download Multiple Choice Questions for Chapters 20

Active Learning Lecture Slides
For use with Classroom Response Systems
Chapter 20:
Testing Hypotheses About Proportions
Intro Stats
Third Edition
by De Veaux, Velleman, Bock
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 1
A P-value indicates
A. the probability that the null hypothesis is
true.
B. the probability that the alternative
hypothesis is true.
C. the probability of the observed statistic
given that the null hypothesis is true.
D. the probability of the observed statistic
given that the alternative hypothesis is
true.
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 2
A P-value indicates
A. the probability that the null hypothesis is
true.
B. the probability that the alternative
hypothesis is true.
C. the probability of the observed statistic
given that the null hypothesis is true.
D. the probability of the observed statistic
given that the alternative hypothesis is
true.
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 3
A small P-value indicates either that the
observation is improbable or that the
probability calculation was based on
incorrect assumptions.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 4
A small P-value indicates either that the
observation is improbable or that the
probability calculation was based on
incorrect assumptions.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 5
In a hypothesis test, we check the
Success/Failure Condition with the observed
proportions.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 6
In a hypothesis test, we check the
Success/Failure Condition with the observed
proportions.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 7
In a hypothesis test, the null hypothesis
represents the status quo.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 8
In a hypothesis test, the null hypothesis
represents the status quo.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 9
According to a June 2004 Gallup poll, 28% of
Americans “said there have been times in the last
year when they haven’t been able to afford medical
care.” Is this proportion higher for black Americans
than for all Americans? In a random sample of 801
black Americans, 38% reported that there had been
times in the last year when they had not been able
to afford medical care. Which type of hypothesis
test would you use?
A. One-tail upper tail
B. One-tail lower tail
C. Two-tail
D. Both A and B
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 10
According to a June 2004 Gallup poll, 28% of
Americans “said there have been times in the last
year when they haven’t been able to afford medical
care.” Is this proportion higher for black Americans
than for all Americans? In a random sample of 801
black Americans, 38% reported that there had been
times in the last year when they had not been able
to afford medical care. Which type of hypothesis
test would you use?
A. One-tail upper tail
B. One-tail lower tail
C. Two-tail
D. Both A and B
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 11
A statistics professor wants to see if more than 80%
of her students enjoyed taking her class. At the end
of the term, she takes a random sample of students
from her large class and asks, in an anonymous
survey, if the students enjoyed taking her class.
Which set of hypotheses should she test?
A. H0: p < 0.80 HA: p > 0.80
B. H0: p = 0.80 HA: p > 0.80
C. H0: p > 0.80 HA: p = 0.80
D. H0: p = 0.80 HA: p < 0.80
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 12
A statistics professor wants to see if more than 80%
of her students enjoyed taking her class. At the end
of the term, she takes a random sample of students
from her large class and asks, in an anonymous
survey, if the students enjoyed taking her class.
Which set of hypotheses should she test?
A. H0: p < 0.80 HA: p > 0.80
B. H0: p = 0.80 HA: p > 0.80
C. H0: p > 0.80 HA: p = 0.80
D. H0: p = 0.80 HA: p < 0.80
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 13
An online catalog company wants on-time delivery
for 90% of the orders they ship. They have been
shipping orders via UPS and FedEx but will switch to
a new, cheaper delivery service (ShipFast) unless
there is evidence that this service cannot meet the
90% on-time goal. As a test the company sends a
random sample of orders via ShipFast, and then
makes follow-up phone calls to see if these orders
arrived on time. Which hypotheses should they test?
A. H0: p < 0.90 HA: p > 0.90
B. H0: p = 0.90 HA: p > 0.90
C. H0: p > 0.90 HA: p = 0.90
D. H0: p = 0.90 HA: p < 0.90
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 14
An online catalog company wants on-time delivery
for 90% of the orders they ship. They have been
shipping orders via UPS and FedEx but will switch to
a new, cheaper delivery service (ShipFast) unless
there is evidence that this service cannot meet the
90% on-time goal. As a test the company sends a
random sample of orders via ShipFast, and then
makes follow-up phone calls to see if these orders
arrived on time. Which hypotheses should they test?
A. H0: p < 0.90 HA: p > 0.90
B. H0: p = 0.90 HA: p > 0.90
C. H0: p > 0.90 HA: p = 0.90
D. H0: p = 0.90 HA: p < 0.90
Copyright © 2009 Pearson Education, Inc.
Slide 20 - 15
Active Learning Lecture Slides
For use with Classroom Response Systems
Chapter 21:
More About Tests
Intro Stats
Third Edition
by De Veaux, Velleman, Bock
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 16
The threshold P-value that determines when
we reject a null hypothesis is called the
A. alpha value.
B. power.
C. beta value.
D. level of significance.
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 17
The threshold P-value that determines when
we reject a null hypothesis is called the
A. alpha value.
B. power.
C. beta value.
D. level of significance.
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 18
We commit a Type II error when the null
hypothesis is true, but we mistakenly reject it.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 19
We commit a Type II error when the null
hypothesis is true, but we mistakenly reject it.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 20
Suppose that a manufacturer is testing one of its
machines to make sure that the machine is producing
more than 97% good parts (H0: p = 0.97 and HA: p >0.97).
The test results in a P-value of 0.102. In reality, the
machine is producing 99% good parts. What probably
happens as a result of our testing?
A. We correctly fail to reject H0.
B. We correctly reject H0.
C. We reject H0, making a Type I error.
D. We fail to reject H0, making a Type I error.
E. We fail to reject H0, making a Type II error.
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 21
Suppose that a manufacturer is testing one of its
machines to make sure that the machine is producing
more than 97% good parts (H0: p = 0.97 and HA: p >0.97).
The test results in a P-value of 0.102. In reality, the
machine is producing 99% good parts. What probably
happens as a result of our testing?
A. We correctly fail to reject H0.
B. We correctly reject H0.
C. We reject H0, making a Type I error.
D. We fail to reject H0, making a Type I error.
E. We fail to reject H0, making a Type II error.
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 22
Which of the following is true about Type I and
Type II errors?
I. Type I errors are always worse than Type II errors.
II. Type II errors are always worse than Type I errors.
III. The severity of Type I and Type II errors depends
on the situation being tested.
A. I only
B. II only
C. III only
D. I and II
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 23
Which of the following is true about Type I and
Type II errors?
I. Type I errors are always worse than Type II errors.
II. Type II errors are always worse than Type I errors.
III. The severity of Type I and Type II errors depends
on the situation being tested.
A. I only
B. II only
C. III only
D. I and II
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 24
We are about to test a hypothesis using data from a
well-designed study. Which is true?
I. A large P-value would be strong evidence against
the null hypothesis.
II. We can set a higher standard of proof by
choosing α = 10% instead of 5%.
III. If we reduce the risk of committing a Type I error,
then the risk of a Type II error will also decrease.
A) None
B) I only
C) II only
D) III only
E) I and II only
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 25
We are about to test a hypothesis using data from a
well-designed study. Which is true?
I. A large P-value would be strong evidence against
the null hypothesis.
II. We can set a higher standard of proof by
choosing α = 10% instead of 5%.
III. If we reduce the risk of committing a Type I error,
then the risk of a Type II error will also decrease.
A) None
B) I only
C) II only
D) III only
E) I and II only
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 26
Suppose that a device advertised to increase a
car’s gas mileage really does not work. We test it
on a small fleet of cars (with H0: not effective), and
our data results in a P-value of 0.004. What
probably happens as a result of our experiment?
A. We correctly fail to reject H0 .
B. We correctly reject H0 .
C. We reject H0, making a Type I error.
D. We reject H0, making a Type II error.
E. We fail to reject H0, committing Type II error.
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 27
Suppose that a device advertised to increase a
car’s gas mileage really does not work. We test it
on a small fleet of cars (with H0: not effective), and
our data results in a P-value of 0.004. What
probably happens as a result of our experiment?
A. We correctly fail to reject H0 .
B. We correctly reject H0 .
C. We reject H0, making a Type I error.
D. We reject H0, making a Type II error.
E. We fail to reject H0, committing Type II error.
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 28
We will test the hypothesis that p = 60% versus
p > 60%. We don’t know it, but actually p is
70%. With which sample size and significance
level will our test have the greatest power?
A. α = 0.01, n = 200
B. α = 0.01, n = 500
C. α = 0.05, n = 200
D. α = 0.05, n = 500
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 29
We will test the hypothesis that p = 60% versus
p > 60%. We don’t know it, but actually p is
70%. With which sample size and significance
level will our test have the greatest power?
A. α = 0.01, n = 200
B. α = 0.01, n = 500
C. α = 0.05, n = 200
D. α = 0.05, n = 500
Copyright © 2009 Pearson Education, Inc.
Slide 21 - 30
Active Learning Lecture Slides
For use with Classroom Response Systems
Chapter 22:
Comparing Two Proportions
Intro Stats
Third Edition
by De Veaux, Velleman, Bock
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 31
Great Britain has a great literary tradition that spans
centuries. One might assume, then, that Britons read
more than citizens of other countries. Some
Canadians, however, feel that a higher percentage of
Canadians than Britons read. A recent Gallup Poll
reported that 86% of 1004 randomly sampled
Canadians read at least one book in the past year,
compared to 81% of 1009 randomly sampled Britons.
If we compare proportions of Britons and Canadians
who read books, the 10% Condition is fulfilled.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 32
Great Britain has a great literary tradition that spans
centuries. One might assume, then, that Britons read
more than citizens of other countries. Some
Canadians, however, feel that a higher percentage of
Canadians than Britons read. A recent Gallup Poll
reported that 86% of 1004 randomly sampled
Canadians read at least one book in the past year,
compared to 81% of 1009 randomly sampled Britons.
If we compare proportions of Britons and Canadians
who read books, the 10% Condition is fulfilled.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 33
Researchers conduct a study to test a potential side
effect of a new allergy medication. A random sample of
160 subjects with allergies was selected for the study.
The new “ improved” Brand I medication was
randomly assigned to 80 subjects, and the current
Brand C medication was randomly assigned to the
other 80 subjects. 14 of the 80 patients with Brand I
reported drowsiness, and 22 of the 80 patients with
Brand C reported drowsiness.
We want of compute a 95% confidence interval for the
difference in proportions of subjects reporting
drowsiness, however we cannot since the samples are
not independent.
A.True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 34
Researchers conduct a study to test a potential side
effect of a new allergy medication. A random sample of
160 subjects with allergies was selected for the study.
The new “ improved” Brand I medication was
randomly assigned to 80 subjects, and the current
Brand C medication was randomly assigned to the
other 80 subjects. 14 of the 80 patients with Brand I
reported drowsiness, and 22 of the 80 patients with
Brand C reported drowsiness.
We want of compute a 95% confidence interval for the
difference in proportions of subjects reporting
drowsiness, however we cannot since the samples are
not independent.
A.True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 35
When testing the difference between two
proportions, we need to check the Success/Failure
Condition. Which of the following is true?
I.
If only the smaller sample passes the Success/Failure
Condition, we can proceed with the test.
II. If only the larger sample passes the Success/Failure
Condition, we can proceed with the test.
III. Both samples must pass the Success/Failure Condition to
proceed with the test.
A. I only
B. II only
C. III only
D. None of the above.
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 36
When testing the difference between two
proportions, we need to check the Success/Failure
Condition. Which of the following is true?
I.
If only the smaller sample passes the Success/Failure
Condition, we can proceed with the test.
II. If only the larger sample passes the Success/Failure
Condition, we can proceed with the test.
III. Both samples must pass the Success/Failure Condition to
proceed with the test.
A. I only
B. II only
C. III only
D. None of the above.
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 37
A relief fund is set up to collect donations for the families
affected by recent storms. A random sample of 400 people
shows that 28% of those 200 who were contacted by
telephone actually made contributions compared to only 18%
of the 200 who received first class mail requests. Which
formula calculates the 95% confidence interval for the
difference in the proportions of people who make donations if
contacted by telephone or first class mail?
(0.23)(0.77)
A. (0.28 - 0.18) ± 1.96
200
B. (0.28 - 0.18) ± 1.96
(0.23)(0.77) (0.23)(0.77)

200
200
C. (0.28 - 0.18) ± 1.96
(0.23)(0.77)
400
D. (0.28 - 0.18) ± 1.96
(0.28)(0.72) (0.18)(0.82)

200
200
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 38
A relief fund is set up to collect donations for the families
affected by recent storms. A random sample of 400 people
shows that 28% of those 200 who were contacted by
telephone actually made contributions compared to only 18%
of the 200 who received first class mail requests. Which
formula calculates the 95% confidence interval for the
difference in the proportions of people who make donations if
contacted by telephone or first class mail?
(0.23)(0.77)
A. (0.28 - 0.18) ± 1.96
200
B. (0.28 - 0.18) ± 1.96
(0.23)(0.77) (0.23)(0.77)

200
200
C. (0.28 - 0.18) ± 1.96
(0.23)(0.77)
400
D. (0.28 - 0.18) ± 1.96
(0.28)(0.72) (0.18)(0.82)

200
200
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 39
A college alumni fund appeals for donations by phoning or
emailing recent graduates. A random sample of 300 alumni
shows that 40% of the 150 who were contacted by telephone
actually made contributions compared to only 30% of the 150
who received email requests. Which formula calculates the
98% confidence interval for the difference in the proportions
of alumni who may make donations if contacted by phone or
by email?
A. (0.40 - 0.30) ± 2.33
B. (0.40 - 0.30) ± 2.33
C. (0.40 - 0.30) ± 2.33
(0.35)(0.65)
150
(0.40)(0.60) (0.30)(0.70)

150
150
(0.35)(0.65)
300
D. (0.40 - 0.30) ± 2.33 (0.35)(0.65)  (0.35)(0.65)
150
150
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 40
A college alumni fund appeals for donations by phoning or
emailing recent graduates. A random sample of 300 alumni
shows that 40% of the 150 who were contacted by telephone
actually made contributions compared to only 30% of the 150
who received email requests. Which formula calculates the
98% confidence interval for the difference in the proportions
of alumni who may make donations if contacted by phone or
by email?
A. (0.40 - 0.30) ± 2.33
B. (0.40 - 0.30) ± 2.33
C. (0.40 - 0.30) ± 2.33
(0.35)(0.65)
150
(0.40)(0.60) (0.30)(0.70)

150
150
(0.35)(0.65)
300
D. (0.40 - 0.30) ± 2.33 (0.35)(0.65)  (0.35)(0.65)
150
150
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 41
A June 2004 public opinion poll asked 1000 randomly
selected adults whether the United States should
decrease the amount of immigration allowed; 49% of
those responding said “yes.” In June 1995, a random
sample of 1000 had found that 65% of adults thought
immigration should be curtailed.
For opinion polls like this, which has more variability,
the percentage of respondents answering “yes” or the
difference in percentages between the two years.
A. The percentage of respondents answering “yes” in
either year.
B. The difference in percentages between the two years.
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 42
A June 2004 public opinion poll asked 1000 randomly
selected adults whether the United States should
decrease the amount of immigration allowed; 49% of
those responding said “yes.” In June 1995, a random
sample of 1000 had found that 65% of adults thought
immigration should be curtailed.
For opinion polls like this, which has more variability,
the percentage of respondents answering “yes” or the
difference in percentages between the two years.
A. The percentage of respondents answering “yes” in
either year.
B. The difference in percentages between the two years.
Copyright © 2009 Pearson Education, Inc.
Slide 22 - 43
Active Learning Lecture Slides
For use with Classroom Response Systems
Chapter 23:
Inferences About Means
Intro Stats
Third Edition
by De Veaux, Velleman, Bock
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 44
Which of the following is not an assumption
or condition that needs to be checked for a
one-sample t-test done on a sample drawn
without replacement?
A. Randomization
B. 10% Condition
C. Success/Failure Condition
D. Nearly Normal Condition
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 45
Which of the following is not an assumption
or condition that needs to be checked for a
one-sample t-test done on a sample drawn
without replacement?
A. Randomization
B. 10% Condition
C. Success/Failure Condition
D. Nearly Normal Condition
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 46
Which statement correctly compares t-distributions to
the normal distribution?
I. t distributions are also mound shaped and symmetric.
II. t distributions have less spread than the normal
distribution.
III. As degrees of freedom increase, the variance of tdistributions becomes smaller.
A. I only
B. II only
C. I and II only
D. I and III only
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 47
Which statement correctly compares t-distributions to
the normal distribution?
I. t distributions are also mound shaped and symmetric.
II. t distributions have less spread than the normal
distribution.
III. As degrees of freedom increase, the variance of tdistributions becomes smaller.
A. I only
B. II only
C. I and II only
D. I and III only
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 48
Which of the following is true about
Student’s t-models?
A. They are unimodal, symmetric, and bell
shaped.
B. They have fatter tails than the Normal
model.
C. As the degrees of freedom increase, the
t-models look more and more like the
Normal Model
D. All of the above.
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 49
Which of the following is true about
Student’s t-models?
A. They are unimodal, symmetric, and bell
shaped.
B. They have fatter tails than the Normal
model.
C. As the degrees of freedom increase, the
t-models look more and more like the
Normal Model
D. All of the above.
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 50
A random sample of 120 classrooms at a
large university found that 70% of them had
been cleaned properly. What is the standard
error of the sample proportion?
A. 0.028
B. 0.042
C. 0.046
D. 0.458
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 51
A random sample of 120 classrooms at a
large university found that 70% of them had
been cleaned properly. What is the standard
error of the sample proportion?
A. 0.028
B. 0.042
C. 0.046
D. 0.458
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 52
A researcher found that a 98% confidence interval
for the mean hours per week spent studying by
college students was (13, 17). Which is true?
A. There is a 98% chance that the mean hours per
week spent studying by college students is
between 13 and 17 hours.
B. We are 98% sure that the mean hours per week
spent studying by college students is between 13
and 17 hours.
C. Students average between 13 and 17 hours per
week studying on 98% of the weeks.
D. 98% of all students spend between 13 and 17
hours studying per week.
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 53
A researcher found that a 98% confidence interval
for the mean hours per week spent studying by
college students was (13, 17). Which is true?
A. There is a 98% chance that the mean hours per
week spent studying by college students is
between 13 and 17 hours.
B. We are 98% sure that the mean hours per week
spent studying by college students is between 13
and 17 hours.
C. Students average between 13 and 17 hours per
week studying on 98% of the weeks.
D. 98% of all students spend between 13 and 17
hours studying per week.
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 54
A professor was curious about her students’ grade point
averages (GPAs). She took a random sample of 15 students and
found a mean GPA of 3.01 with a standard deviation of 0.534.
Which of the following formulas gives a 99% confidence interval
for the mean GPA of the professor’s students?
0.534
15
•
3.01± 2.947
•
0.534
3.01± 2.977
15
•
3.01± 2.576
0.534
15
•
3.01± 2.947
0.534
14
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 55
A professor was curious about her students’ grade point
averages (GPAs). She took a random sample of 15 students and
found a mean GPA of 3.01 with a standard deviation of 0.534.
Which of the following formulas gives a 99% confidence interval
for the mean GPA of the professor’s students?
0.534
15
•
3.01± 2.947
•
0.534
3.01± 2.977
15
•
3.01± 2.576
0.534
15
•
3.01± 2.947
0.534
14
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 56
A coffee house owner knows that customers pour different
amounts of coffee into their cups. She samples cups from 10
costumers she believes to be representative of the customers
and weighs the cups, finding a mean of 12.5 ounces and
standard deviation of 0.5 ounces. Assuming these cups of
coffee can be considered a random sample of all cups of coffee
which of the following formulas gives a 95% confidence interval
for the mean weight of all cups of coffee?
A. 12.5 ± 1.96
0.5
10
B. 12.5 ± 2.228
0.5
10
C. 12.5 ± 2.262
0.5
10
D. 12.5 ± 2.262
0.5
9
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 57
A coffee house owner knows that customers pour different
amounts of coffee into their cups. She samples cups from 10
costumers she believes to be representative of the customers
and weighs the cups, finding a mean of 12.5 ounces and
standard deviation of 0.5 ounces. Assuming these cups of
coffee can be considered a random sample of all cups of coffee
which of the following formulas gives a 95% confidence interval
for the mean weight of all cups of coffee?
A. 12.5 ± 1.96
0.5
10
B. 12.5 ± 2.228
0.5
10
C. 12.5 ± 2.262
0.5
10
D. 12.5 ± 2.262
0.5
9
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 58
A wildlife biologist wants to determine the mean weight of adult
red squirrels. She captures 10 squirrels she believes to be
representative of the species and weighs them, finding a mean of
12.32 grams and standard deviation of 1.88gm. Assuming these
squirrels can be considered a random sample of all red squirrels
which of the following formulas gives a 95% confidence interval
for the mean weight of all squirrels?
1.88
A. 12.32 ± 1.96
10
B. 12.32 ± 2.228
1.88
10
C. 12.32 ± 2.262
1.88
10
D. 12.32 ± 2.268
1.88
9
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 59
A wildlife biologist wants to determine the mean weight of adult
red squirrels. She captures 10 squirrels she believes to be
representative of the species and weighs them, finding a mean of
12.32 grams and standard deviation of 1.88gm. Assuming these
squirrels can be considered a random sample of all red squirrels
which of the following formulas gives a 95% confidence interval
for the mean weight of all squirrels?
1.88
A. 12.32 ± 1.96
10
B. 12.32 ± 2.228
1.88
10
C. 12.32 ± 2.262
1.88
10
D. 12.32 ± 2.268
1.88
9
Copyright © 2009 Pearson Education, Inc.
Slide 23 - 60
Active Learning Lecture Slides
For use with Classroom Response Systems
Chapter 24:
Comparing Means
Intro Stats
Third Edition
by De Veaux, Velleman, Bock
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 61
A philosophy professor wants to find out whether the mean age
of the men in his large lecture class is equal to the mean age of
the women in his class. After collecting data from his students,
the professor tested the hypothesis H0 : M - W = 0 against the
alternative HA : M - W ­ 0 . The P-value for the test was 0.003.
Which is true?
A. There is a 0.3% chance that the mean age for the men is equal
to the mean age for the women.
B. There is a 0.3% chance that the mean age for the men is
different from the mean age of the women.
C. It is very unlikely that the professor would see results like
these if the mean age of men was equal to the mean age of
women.
D. There is a 0.3% chance that another sample will give these
same results.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 62
A philosophy professor wants to find out whether the mean age
of the men in his large lecture class is equal to the mean age of
the women in his class. After collecting data from his students,
the professor tested the hypothesis H0 : M - W = 0 against the
alternative HA : M - W ­ 0 . The P-value for the test was 0.003.
Which is true?
A. There is a 0.3% chance that the mean age for the men is equal
to the mean age for the women.
B. There is a 0.3% chance that the mean age for the men is
different from the mean age of the women.
C. It is very unlikely that the professor would see results like
these if the mean age of men was equal to the mean age of
women.
D. There is a 0.3% chance that another sample will give these
same results.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 63
Absorption rates into the body are important considerations when
manufacturing a generic version of a brand-name drug. A
pharmacist read that the absorption rate into the body of a new
generic drug (G) is the same as its brand-name counterpart (B).
She has a researcher friend of hers run a small experiment to test
H0 : G - B = 0 against the alternative HA : G - B ­ 0. Which of
the following would be a Type I error?
A. Deciding that the absorption rates are different, when in fact
they are not.
B. Deciding that the absorption rates are different, when in fact
they are.
C. Deciding that the absorption rates are the same, when in fact
they are not.
D. Deciding that the absorption rates are the same, when in fact
they are.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 64
Absorption rates into the body are important considerations when
manufacturing a generic version of a brand-name drug. A
pharmacist read that the absorption rate into the body of a new
generic drug (G) is the same as its brand-name counterpart (B).
She has a researcher friend of hers run a small experiment to test
H0 : G - B = 0 against the alternative HA : G - B ­ 0. Which of
the following would be a Type I error?
A. Deciding that the absorption rates are different, when in fact
they are not.
B. Deciding that the absorption rates are different, when in fact
they are.
C. Deciding that the absorption rates are the same, when in fact
they are not.
D. Deciding that the absorption rates are the same, when in fact
they are.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 65
Doctors at a technology research facility randomly assigned
equal numbers of people to use computer keyboards in two
rooms. In one room a group of people typed a manuscript using
standard keyboards, while in the other room people typed the
same manuscript using ergonomic keyboards to see if those
people could type more words per minute. After collecting data
for several days the researchers tested the hypothesis
H0 : 1 - 2 = 0 against the one-tail alternative and found a P-value
of 0.22. Which is true?
A) The people using ergonomic keyboards type 22% more words
per minute.
B) There’s a 22% chance that people using ergonomic
keyboards type more words per minute.
C) There’s a 22% chance that there’s really no difference in
typing speed.
D) There’s a 22% chance another experiment will give these
same results.
E) None of these.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 66
Doctors at a technology research facility randomly assigned
equal numbers of people to use computer keyboards in two
rooms. In one room a group of people typed a manuscript using
standard keyboards, while in the other room people typed the
same manuscript using ergonomic keyboards to see if those
people could type more words per minute. After collecting data
for several days the researchers tested the hypothesis
H0 : 1 - 2 = 0 against the one-tail alternative and found a P-value
of 0.22. Which is true?
A) The people using ergonomic keyboards type 22% more words
per minute.
B) There’s a 22% chance that people using ergonomic
keyboards type more words per minute.
C) There’s a 22% chance that there’s really no difference in
typing speed.
D) There’s a 22% chance another experiment will give these
same results.
E) None of these.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 67
Which of the following is not an assumption or condition
that needs to be checked for a two-sample t-test for the
difference between two means?
A. Independent Groups
B. Randomization
C. 10% Condition
D. Nearly Normal Condition
E. All of the above must be checked.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 68
Which of the following is not an assumption or condition
that needs to be checked for a two-sample t-test for the
difference between two means?
A. Independent Groups
B. Randomization
C. 10% Condition
D. Nearly Normal Condition
E. All of the above must be checked.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 69
Trainers need to estimate the level of fat in athletes to
ensure good health. Initial tests were based on a small
sample but now the trainers double the sample size for
a follow-up test. The main purpose of the larger sample
is to…
A. reduce response bias.
B. reduce non-response bias.
C. decrease the variability in the population.
D. reduce confounding due to other variables.
E. decrease the standard deviation of the sampling
model.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 70
Trainers need to estimate the level of fat in athletes to
ensure good health. Initial tests were based on a small
sample but now the trainers double the sample size for
a follow-up test. The main purpose of the larger sample
is to…
A. reduce response bias.
B. reduce non-response bias.
C. decrease the variability in the population.
D. reduce confounding due to other variables.
E. decrease the standard deviation of the sampling
model.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 71
Based on data from two very large independent
samples, two students tested a hypothesis about
equality of population means using α = 0.02. One
student used a one-tail test and rejected the null
hypothesis, but the other used a two-tail test and failed
to reject the null. Which of these might have been their
calculated value of t ?
A. 1.22
B. 1.55
C. 2.22
D. 1.88
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 72
Based on data from two very large independent
samples, two students tested a hypothesis about
equality of population means using α = 0.02. One
student used a one-tail test and rejected the null
hypothesis, but the other used a two-tail test and failed
to reject the null. Which of these might have been their
calculated value of t ?
A. 1.22
B. 1.55
C. 2.22
D. 1.88
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 73
A contact lens wearer read that the producer of a new contact lens
boasts that their lenses are cheaper than contact lenses from
another popular company. The null hypothesis H0 : old - new = 0
is tested against the alternative HA : old - new > 0 . Which of the
following would be a Type II error?
A. Deciding that the new lenses are cheaper, when in fact they
really are.
B. Deciding that the new lenses are cheaper, when in fact they
are not.
C. Deciding that the new lenses are not really cheaper, when in
fact they are.
D. Deciding that the new lenses are not really cheaper, when in
fact they are not.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 74
A contact lens wearer read that the producer of a new contact lens
boasts that their lenses are cheaper than contact lenses from
another popular company. The null hypothesis H0 : old - new = 0
is tested against the alternative HA : old - new > 0 . Which of the
following would be a Type II error?
A. Deciding that the new lenses are cheaper, when in fact they
really are.
B. Deciding that the new lenses are cheaper, when in fact they
are not.
C. Deciding that the new lenses are not really cheaper, when in
fact they are.
D. Deciding that the new lenses are not really cheaper, when in
fact they are not.
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 75
There is never a time when assuming equal
variances makes sense.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 76
There is never a time when assuming equal
variances makes sense.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 24 - 77
Active Learning Lecture Slides
For use with Classroom Response Systems
Chapter 25:
Paired Samples and Blocks
Intro Stats
Third Edition
by De Veaux, Velleman, Bock
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 78
To construct a confidence interval for the mean of
paired data, we
A. treat the data as if it is two independent samples
and construct a two-sample t-interval.
B. find the differences between the data and construct
a one-sample t-interval.
C. find the proportion of the data pairs with increases
and construct a one-proportion z-interval.
D. cannot do anything to construct a confidence
interval.
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 79
To construct a confidence interval for the mean of
paired data, we
A. treat the data as if it is two independent samples
and construct a two-sample t-interval.
B. find the differences between the data and construct
a one-sample t-interval.
C. find the proportion of the data pairs with increases
and construct a one-proportion z-interval.
D. cannot do anything to construct a confidence
interval.
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 80
Which of the following is not an assumption or
condition that needs to be checked for
a paired t-interval?
A. Paired Data
B. Independent Groups
C. Randomization
D. 10% Condition
E. Nearly Normal Condition
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 81
Which of the following is not an assumption or
condition that needs to be checked for
a paired t-interval?
A. Paired Data
B. Independent Groups
C. Randomization
D. 10% Condition
E. Nearly Normal Condition
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 82
Do twins score the same on IQ tests? The following table shows IQ
scores for a random sample of twins:
Twin A
Twin B
84
77
106
104
113
106
112
113
97
102
115
103
121
117
We want to conduct the appropriate hypothesis test to test if twins
score the same on IQ tests. If d = Twin A IQ – Twin B IQ, and
H0 : d = 0 then,
A.
H A : d  0
B.
HA : d > 0
C.
HA : d < 0
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 83
Do twins score the same on IQ tests? The following table shows IQ
scores for a random sample of twins:
Twin A
Twin B
84
77
106
104
113
106
112
113
97
102
115
103
121
117
We want to conduct the appropriate hypothesis test to test if twins
score the same on IQ tests. If d = Twin A IQ – Twin B IQ, and
H0 : d = 0 then,
A.
H A : d  0
B.
HA : d > 0
C.
HA : d < 0
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 84
Before you took this course, you probably heard many stories
about intro stats courses. Oftentimes parents of students have
had bad experiences with intro stats courses and pass on their
anxieties to their children. To test whether actually taking intro
stats decreases students’ anxieties about statistics, a statistics
instructor gave a test to rate student anxiety at the beginning
and end of his course. Anxiety levels were measured on a scale
of 0-10. We decide to choose 20 students randomly from a class
of 180 students. If we proceed in this manner, which condition
is violated:
A. Independence
B. Randomization
C. 10% Condition
D. Nearly Normal Condition
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 85
Before you took this course, you probably heard many stories
about intro stats courses. Oftentimes parents of students have
had bad experiences with intro stats courses and pass on their
anxieties to their children. To test whether actually taking intro
stats decreases students’ anxieties about statistics, a statistics
instructor gave a test to rate student anxiety at the beginning
and end of his course. Anxiety levels were measured on a scale
of 0-10. We decide to choose 20 students randomly from a class
of 180 students. If we proceed in this manner, which condition
is violated:
A. Independence
B. Randomization
C. 10% Condition
D. Nearly Normal Condition
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 86
A paired design is an example of
A. Blinding
B. Blocking
C. Confounding
D. Matching
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 87
A paired design is an example of
A. Blinding
B. Blocking
C. Confounding
D. Matching
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 88
Random samples of 50 men and 50 women are asked
to imagine buying a birthday present for their best
friend. We want to estimate the difference in how
much they are willing to spend. We would use a
A. Two-sample t hypothesis test.
B. Two-sample t confidence interval.
C. Paired t hypothesis test.
D. Paired t confidence interval.
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 89
Random samples of 50 men and 50 women are asked
to imagine buying a birthday present for their best
friend. We want to estimate the difference in how
much they are willing to spend. We would use a
A. Two-sample t hypothesis test.
B. Two-sample t confidence interval.
C. Paired t hypothesis test.
D. Paired t confidence interval.
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 90
Are parents equally strict with boys and girls? In a
random sample of families, researchers asked a
brother and sister from each family to rate how strict
their parents were. We would use a
A. Two-sample t hypothesis test.
B. Two-sample t confidence interval.
C. Paired t hypothesis test.
D. Paired t confidence interval.
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 91
Are parents equally strict with boys and girls? In a
random sample of families, researchers asked a
brother and sister from each family to rate how strict
their parents were. We would use a
A. Two-sample t hypothesis test.
B. Two-sample t confidence interval.
C. Paired t hypothesis test.
D. Paired t confidence interval.
Copyright © 2009 Pearson Education, Inc.
Slide 25 - 92
Active Learning Lecture Slides
For use with Classroom Response Systems
Chapter 26:
Comparing Counts
Intro Stats
Third Edition
by De Veaux, Velleman, Bock
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 93
Which of the following is not an assumption
or condition that needs to be checked for
chi-square tests?
A. Counted Data
B. Randomization
C. Success/Failure Condition
D. Expected Cell Frequency
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 94
Which of the following is not an assumption
or condition that needs to be checked for
chi-square tests?
A. Counted Data
B. Randomization
C. Success/Failure Condition
D. Expected Cell Frequency
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 95
Which of the following is not true about chi-square
models?
A. They are unimodal and right skewed.
B. They can only take on nonnegative values.
C. They have degrees of freedom like t-models,
although the degrees of freedom are calculated
differently.
D. As the degrees of freedom increase, the chisquare models look more and more like the
Normal.
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 96
Which of the following is not true about chi-square
models?
A. They are unimodal and right skewed.
B. They can only take on nonnegative values.
C. They have degrees of freedom like t-models,
although the degrees of freedom are calculated
differently.
D. As the degrees of freedom increase, the chisquare models look more and more like the
Normal.
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 97
How many degrees of freedom are there for a chisquare test of independence with five rows and
six columns?
A. 4
B. 5
C. 20
D. 24
E. 30
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 98
How many degrees of freedom are there for a chisquare test of independence with five rows and
six columns?
A. 4
B. 5
C. 20
D. 24
E. 30
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 99
A test comparing the distribution of counts
for two or more groups on the same
categorical variable is called a test of
A. Independence
B. Homogeneity
C. Randomization
D. Normalization
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 100
A test comparing the distribution of counts
for two or more groups on the same
categorical variable is called a test of
A. Independence
B. Homogeneity
C. Randomization
D. Normalization
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 101
Whenever we reject the null hypothesis when
conducting a test for homogeneity, it is a
good idea to
A. change the sample size.
B. change the degrees of freedom.
C. examine the residuals.
D. leave the answer as is.
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 102
Whenever we reject the null hypothesis when
conducting a test for homogeneity, it is a
good idea to
A. change the sample size.
B. change the degrees of freedom.
C. examine the residuals.
D. leave the answer as is.
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 103
The degrees of freedom for chi-square tests
grow with the sample size.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 104
The degrees of freedom for chi-square tests
grow with the sample size.
A. True
B. False
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 105
Goodness of fit tests compare
A. the observed distribution of a single categorical
variable to an expected distribution based on a
theory or model.
B. the distribution of several groups for the same
categorical variable.
C. counts from a single group for evidence of an
association between two categorical variables.
D. None of the above.
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 106
Goodness of fit tests compare
A. the observed distribution of a single categorical
variable to an expected distribution based on a
theory or model.
B. the distribution of several groups for the same
categorical variable.
C. counts from a single group for evidence of an
association between two categorical variables.
D. None of the above.
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 107
Could eye color be a warning signal for hearing loss
in patients suffering from meningitis? British
researcher Helen Cullington recorded the eye color of
130 deaf patients, and noted whether the patient’s
deafness had developed following treatment
for meningitis. Her data are summarized in the table
below. After setting up the appropriate hypothesis,
what is the P-value?
Eye Color
Light
Dark
Deafness related to …
Meningitis
0ther
30
72
2
26
A. 0.15
B. 0.015
C. 0.0015
D. 1.5
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 108
Could eye color be a warning signal for hearing loss
in patients suffering from meningitis? British
researcher Helen Cullington recorded the eye color of
130 deaf patients, and noted whether the patient’s
deafness had developed following treatment
for meningitis. Her data are summarized in the table
below. After setting up the appropriate hypothesis,
what is the P-value?
Eye Color
Light
Dark
Deafness related to …
Meningitis
0ther
30
72
2
26
A. 0.15
B. 0.015
C. 0.0015
D. 1.5
Copyright © 2009 Pearson Education, Inc.
Slide 26 - 109