Test Bank for An Introduction to Statistics An Active Learning Approach, 2nd Edition
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Medical Microbiology For Healthcare Professionals
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University Of Alberta (UofA)
Test Bank for An Introduction to Statistics An Active Learning Approach, 2nd Edition
Test Bank
Chapter 1: Introduction to Statistics and Frequency Distributions
Multiple Choice
1. After a statistics class, Dr. Johnson asked all 51 of her students the degree to which they felt
statistics were g...
test bank for an introduction to statistics an active learning approach
test bank for an introduction to statistics an active learning approach
2nd editiontest bank for an introduction t
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Test Bank for An Introduction to Statistics An
Active Learning Approach, 2nd Edition, Kieth A.
Carlson, Jennifer R. Winquist
,Test Bank
Chapter 1: Introduction to Statistics and Frequency Distributions
Multiple Choice
1. After a statistics class, Dr. Johnson asked all 51 of her students the degree to which they felt
statistics were going to be useful in their eventual career. She had all of her students respond to
the following question, “Statistics will be very useful in my future profession,” using the
following scale: 1 = not at all useful and 7 = very useful. She found that the average response
was a 4.9. Given that the mean 4.9 was based on all of her students, the 4.9 would be called
.
A. a statistic
B. a parameter
C. sampling error
Ans: B
Learning Objective: Terms parameter
2. After a statistics class, Dr. Johnson asked all 51 of her students the degree to which they felt
statistics were going to be useful in their eventual career. She had all of her students respond to
the following question, “Statistics will be very useful in my future profession,” using the
following scale: 1 = not at all useful and 7 = very useful. She found that the average response
was a 4.9. The purpose of Dr. Johnson’s survey is best described as .
A. sampling error
B. descriptive
C. inferential
Ans: B
Learning Objective: Terms descriptive statistics
3. A cognitive psychologist studying reading comprehension wanted to know what would
happen if all college students were taught better reading strategies. She obtained a sample of 40
college students from the introductory psychology class and taught 20 of them effective reading
strategies. The other 20 students were given a placebo treatment. She then gave all 40 students a
standardized reading comprehension test. The mean score on the reading test for those taught the
reading strategies was 49, with a standard deviation of 4. The mean score for those receiving the
placebo treatment was 44, with a standard deviation of 3.8. The purpose of this study is best
described as:
,A. descriptive
B. inferential
Ans: B
Learning Objective: Terms inferential statistics
4. A cognitive psychologist studying reading comprehension wanted to know what would
happen if all college students were taught better reading strategies. She obtained a sample of 40
college students from the introductory psychology class and taught 20 of them effective reading
strategies. The other 20 students were given a placebo treatment. She then gave all 40 students a
standardized reading comprehension test. The mean score on the reading test for those taught the
reading strategies was 49, with a standard deviation of 4. The mean score for those receiving the
placebo treatment was 44, with a standard deviation of 3.8.The sample of college students was
intended to represent all college students, therefore the values of 49 and 44 would be called
.
A. statistic
B. parameters
Ans: A
Learning Objective: Terms statistic
5. After their medical appointments with her, Dr. Jackson asked all 42 of her patients if they
were satisfied with their medical appointment. She had all of her patients rate their overall
satisfaction by answering the following question, “How satisfied are you with the medical
appointment you just had?” 1 = not at all satisfied; 7 = completely satisfied. She found that the
average response was a satisfaction score of 5.2. Given that the mean satisfaction score of 5.2
was based on all of her patients, the 5.2 would be called .
A. a statistic
B. a parameter
C. sampling error
Ans: B
Learning Objective: Terms parameter
6. After their medical appointments with her, Dr. Jackson asked all 42 of her patients if they
were satisfied with their medical appointment. She had all of her patients rate their overall
satisfaction by answering the following question, “How satisfied are you with the medical
appointment you just had?” 1 = not at all satisfied; 7 = completely satisfied. She found that the
average response was a satisfaction score of 5.2. The purpose of Dr. Jackson’s survey is best
described as .
A. sampling error
, B. descriptive
C. inferential
Ans: B
Learning Objective: Terms descriptive statistics
7. A U.S. Senator from Indiana wanted to know what all her constituents thought about the
Clean Air Act that was coming up for a vote in the Senate. She sent a letter to a sample of 257
Indiana voters asking them if they supported the Clean Air Act even if it meant they would have
to pay higher prices for gasoline. The results indicated that 39% of the sample supported the
Clean Air Act even if it meant higher gasoline prices. The purpose of this survey is best
described as :
A. descriptive
B. inferential
C. sampling error
Ans: B
Learning Objective: Terms interential statistics
8. A U.S. Senator from Indiana wanted to know what all her constituents thought about the
Clean Air Act that was coming up for a vote in the Senate. She sent a letter to a sample of 257
Indiana voters asking them if they supported the Clean Air Act even if it meant they would have
to pay higher prices for gasoline. The results indicated that 39% of the sample supported the
Clean Air Act even if it meant higher gasoline prices. The sample of Indiana voters was intended
to represent all Indiana voters, therefore the value of 39% would be called .
A. a parameter
B. sampling error
C. a statistic
Ans: C
Learning Objective: Terms statistic
9. Researchers use samples to estimate population parameters because it is rarely feasible to
obtain data from an entire population. Sample statistics estimate population parameters. The
discrepancy between sample statistics and population parameters is called:
A. statistical power
B. Type I error
C. Type II error
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