TEST BANK b b
Introduction to Statistical Investigations,
b b b b
2nd Edition Nathan Tintle; Beth L. Chance
b b b b b b
Chapters 1 - 11, Complete
b b b b b
FOR INSTRUCTOR USE ONLY
b b b
,TABLE OF CONTENTS
b b b
Chapter 1 – Significance: How Strong is the Evidence
b b b b b b b b b
Chapter 2 – Generalization: How Broadly Do the Results Apply?
b b b b b b b b b b
Chapter 3 – Estimation: How Large is the Effect?
b b b b b b b b b
Chapter 4 – Causation: Can We Say What Caused the Effect?
b b b b b b b b b b b
Chapter 5 – Comparing Two Proportions
b b b b b b
Chapter 6 – Comparing Two Means
b b b b b b
Chapter 7 – Paired Data: One Quantitative Variable
b b b b b b b b
Chapter 8 – Comparing More Than Two Proportions
b b b b b b b b
Chapter 9 – Comparing More Than Two Means
b b b b b b b b
Chapter 10 – Two Quantitative Variables
b b b b b b
Chapter 11 – Modeling Randomness
b b b b
FOR INSTRUCTOR USE ONLY
b b b
,Chapter 1 b
Note: TE = Text entry
bb b b b b TE-N = Text entry - NumericMa
b b b b b b
b = Matching b MS = Multiple select b b b
MC = Multiple choice b b b TF = True-FalseE =
b b b b
b Easy, M = Medium, H = Hard b b b b b b
CHAPTER 1 LEARNING OBJECTIVES b b b
CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
b b b b b b b b b b b b b b
CLO1-2: Calculate and interpret a p-value, and state the strength of evidence it provides againstthe null
b b b b b b b b b b b b b b b b
hypothesis. b
CLO1-3: Calculate a standardized statistic for a single proportion and evaluate the strength ofevidence it
b b b b b b b b b b b b b b b
provides against a null hypothesis.
b b b b b
CLO1-4: Describe how the distance of the observed statistic from the parameter value specifiedby the null
b b b b b b b b b b b b b b b b
hypothesis, sample size, and one- vs. two-sided tests affect the strength of evidence against the null
b b b b b b b b b b b b b b b b
hypothesis. b
CLO1-5: Describe how to carry out a theory-based, one-proportion z-test.
b b b b b b b b b
Section 1.1: Introduction to Chance Models b b b b b
LO1.1-1: Recognize the difference between parameters and statistics.
b b b b b b b
LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-dom choice
b b b b b b b b b b b b b b b b b b
between two events.
b b b
LO1.1-3: Use the One Proportion applet to carry out the coin tossing simulation.
b b b b b b b b b b b b
LO1.1-4: Identify whether or not study results are statistically significant and whether or not thechance
b b b b b b b b b b b b b b b
model is a plausible explanation for the data.
b b b b b b b b
LO1.1-5: Implement the 3S strategy: find a statistic, simulate results from a chance model, and comment
b b b b b b b b b b b b b b b
on strength of evidence against observed study results happening by chance alone.
b b b b b b b b b b b b
LO1.1-6: Differentiate between saying the chance model is plausible and the chance model is the correct
b b b b b b b b b b b b b b b
explanation for the observed data.
b b b b b
FOR INSTRUCTOR USE ONLY b b b
, 1-2 Test Bank for Introduction to Statistical Investigations, 2nd Edition
b b b b b b b b
Questions 1 through 4:
b b b
Do red uniform wearers tend to win more often than those wearing blue uniforms in Taekwondo
b b b b b b b b b b b b b b b
matches where competitors are randomly assigned to wear either a red or blue uniform? In a
b b b b b b b b b b b b b b b b
sample of 80 Taekwondo matches, there were 45 matches where thered uniform wearer won.
b b b b b b b b b b b b b b b
1. What is the parameter of interest for this study?
b b b b b b b b
A. The long-run proportion of Taekwondo matches in which the red uniform wearerwins
b b b b b b b b b b b b
B. The proportion of matches in which the red uniform wearer wins in a sample of 80
b b b b b b b b b b b b b b b
Taekwondo matches b b
C. Whether the red uniform wearer wins a match b b b b b b b
D. 0.50 b
Ans: A; LO: 1.1-1; Difficulty: Easy; Type: MC
b b b b b b b
2. What is the statistic for this study?
b b b b b b
A. The long-run proportion of Taekwondo matches in which the red uniform wearerwins
b b b b b b b b b b b b
B. The proportion of matches in which the red uniform wearer wins in a sample of 80
b b b b b b b b b b b b b b b
Taekwondo matches b b
C. Whether the red uniform wearer wins a match b b b b b b b
D. 0.50 b
Ans: B; LO: 1.1-1; Difficulty: Easy; Type: MC
b b b b b b b
3. Given below is the simulated distribution of the number of ―red wins‖ that could happen by chance
b b b b b b b b b b b b b b b b
alone in a sample of 80 matches. Based on this simulation, is our observed result statistically
b b b b b b b b b b b b b b b b
significant?
b
A. Yes, since 45 is larger than 40. b b b b b b
B. Yes, since the height of the dotplot above 45 is smaller than the height of thedotplot
b b b b b b b b b b b b b b b b
above 40. b b
C. No, since 45 is a fairly typical outcome if the color of the winner‘s uniform was
b b b b b b b b b b b b b b b
determined by chance alone.
b b b b
FOR INSTRUCTOR USE ONLY b b b
Introduction to Statistical Investigations,
b b b b
2nd Edition Nathan Tintle; Beth L. Chance
b b b b b b
Chapters 1 - 11, Complete
b b b b b
FOR INSTRUCTOR USE ONLY
b b b
,TABLE OF CONTENTS
b b b
Chapter 1 – Significance: How Strong is the Evidence
b b b b b b b b b
Chapter 2 – Generalization: How Broadly Do the Results Apply?
b b b b b b b b b b
Chapter 3 – Estimation: How Large is the Effect?
b b b b b b b b b
Chapter 4 – Causation: Can We Say What Caused the Effect?
b b b b b b b b b b b
Chapter 5 – Comparing Two Proportions
b b b b b b
Chapter 6 – Comparing Two Means
b b b b b b
Chapter 7 – Paired Data: One Quantitative Variable
b b b b b b b b
Chapter 8 – Comparing More Than Two Proportions
b b b b b b b b
Chapter 9 – Comparing More Than Two Means
b b b b b b b b
Chapter 10 – Two Quantitative Variables
b b b b b b
Chapter 11 – Modeling Randomness
b b b b
FOR INSTRUCTOR USE ONLY
b b b
,Chapter 1 b
Note: TE = Text entry
bb b b b b TE-N = Text entry - NumericMa
b b b b b b
b = Matching b MS = Multiple select b b b
MC = Multiple choice b b b TF = True-FalseE =
b b b b
b Easy, M = Medium, H = Hard b b b b b b
CHAPTER 1 LEARNING OBJECTIVES b b b
CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
b b b b b b b b b b b b b b
CLO1-2: Calculate and interpret a p-value, and state the strength of evidence it provides againstthe null
b b b b b b b b b b b b b b b b
hypothesis. b
CLO1-3: Calculate a standardized statistic for a single proportion and evaluate the strength ofevidence it
b b b b b b b b b b b b b b b
provides against a null hypothesis.
b b b b b
CLO1-4: Describe how the distance of the observed statistic from the parameter value specifiedby the null
b b b b b b b b b b b b b b b b
hypothesis, sample size, and one- vs. two-sided tests affect the strength of evidence against the null
b b b b b b b b b b b b b b b b
hypothesis. b
CLO1-5: Describe how to carry out a theory-based, one-proportion z-test.
b b b b b b b b b
Section 1.1: Introduction to Chance Models b b b b b
LO1.1-1: Recognize the difference between parameters and statistics.
b b b b b b b
LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-dom choice
b b b b b b b b b b b b b b b b b b
between two events.
b b b
LO1.1-3: Use the One Proportion applet to carry out the coin tossing simulation.
b b b b b b b b b b b b
LO1.1-4: Identify whether or not study results are statistically significant and whether or not thechance
b b b b b b b b b b b b b b b
model is a plausible explanation for the data.
b b b b b b b b
LO1.1-5: Implement the 3S strategy: find a statistic, simulate results from a chance model, and comment
b b b b b b b b b b b b b b b
on strength of evidence against observed study results happening by chance alone.
b b b b b b b b b b b b
LO1.1-6: Differentiate between saying the chance model is plausible and the chance model is the correct
b b b b b b b b b b b b b b b
explanation for the observed data.
b b b b b
FOR INSTRUCTOR USE ONLY b b b
, 1-2 Test Bank for Introduction to Statistical Investigations, 2nd Edition
b b b b b b b b
Questions 1 through 4:
b b b
Do red uniform wearers tend to win more often than those wearing blue uniforms in Taekwondo
b b b b b b b b b b b b b b b
matches where competitors are randomly assigned to wear either a red or blue uniform? In a
b b b b b b b b b b b b b b b b
sample of 80 Taekwondo matches, there were 45 matches where thered uniform wearer won.
b b b b b b b b b b b b b b b
1. What is the parameter of interest for this study?
b b b b b b b b
A. The long-run proportion of Taekwondo matches in which the red uniform wearerwins
b b b b b b b b b b b b
B. The proportion of matches in which the red uniform wearer wins in a sample of 80
b b b b b b b b b b b b b b b
Taekwondo matches b b
C. Whether the red uniform wearer wins a match b b b b b b b
D. 0.50 b
Ans: A; LO: 1.1-1; Difficulty: Easy; Type: MC
b b b b b b b
2. What is the statistic for this study?
b b b b b b
A. The long-run proportion of Taekwondo matches in which the red uniform wearerwins
b b b b b b b b b b b b
B. The proportion of matches in which the red uniform wearer wins in a sample of 80
b b b b b b b b b b b b b b b
Taekwondo matches b b
C. Whether the red uniform wearer wins a match b b b b b b b
D. 0.50 b
Ans: B; LO: 1.1-1; Difficulty: Easy; Type: MC
b b b b b b b
3. Given below is the simulated distribution of the number of ―red wins‖ that could happen by chance
b b b b b b b b b b b b b b b b
alone in a sample of 80 matches. Based on this simulation, is our observed result statistically
b b b b b b b b b b b b b b b b
significant?
b
A. Yes, since 45 is larger than 40. b b b b b b
B. Yes, since the height of the dotplot above 45 is smaller than the height of thedotplot
b b b b b b b b b b b b b b b b
above 40. b b
C. No, since 45 is a fairly typical outcome if the color of the winner‘s uniform was
b b b b b b b b b b b b b b b
determined by chance alone.
b b b b
FOR INSTRUCTOR USE ONLY b b b
