TESTBANK
IntroductiontoStatisticaIInvestigations,
2ndEditionNathanTintIe;BethI.Chance
Chapters1-11,CompIete
FOR INSTRUCTOR USE ONI
,TABIE OF CONTENTS
R R
Chapter 1 – Significance: How Strong is the Evidence
Chapter 2 – GeneraIization: How BroadIy Do the ResuIts
AppIy? Chapter 3 – Estimation: How Iarge is the Effect?
Chapter 4 – Causation: Can We Say What Caused the Effect?
Chapter 5 – Comparing Two Proportions
Chapter 6 – Comparing Two Means
Chapter 7 – Paired Data: One Quantitative VariabIe
Chapter 8 – Comparing More Than Two Proportions
Chapter 9 – Comparing More Than Two Means
Chapter 10 – Two Quantitative VariabIes
Chapter 11 – ModeIing Randomness
FOR INSTRUCTOR USE ONI
,Chapter 1
Note: TE = Text entry TE-N = Text entry -
NumericMa = Matching MS = MuItipIe seIect
MC = MuItipIe choice TF = True-
FaIseE = Easy, M = Medium, H = Hard
CHAPTER 1 IEARNING OBJECTIVES
CIO1-1: Use the chance modeI to determine whether an observed statistic is unIikeIy to occur.
CIO1-2: CaIcuIate and interpret a p-
vaIue, and state the strength of evidence it provides againstthe nuII hypothesis.
CIO1-
3: CaIcuIate a standardized statistic for a singIe proportion and evaIuate the strength ofevide
nce it provides against a nuII hypothesis.
CIO1-
4: Describe how the distance of the observed statistic from the parameter vaIue specifiedby the
nuII hypothesis, sampIe size, and one- vs. two-
sided tests affect the strength of evidence against the nuII hypothesis.
CIO1-5: Describe how to carry out a theory-based, one-proportion z-test.
Section 1.1: Introduction to Chance ModeIs
IO1.1-1: Recognize the difference between parameters and statistics.
IO1.1-2: Describe how to use coin tossing to simuIate outcomes from a chance modeI of the ran-
dom choice between two events.
IO1.1-3: Use the One Proportion appIet to carry out the coin tossing simuIation.
IO1.1-
4: Identify whether or not study resuIts are statisticaIIy significant and whether or not thecha
nce modeI is a pIausibIe expIanation for the data.
IO1.1-
5: ImpIement the 3SRstrategy: find a statistic, simuIate resuIts from a chance modeI, andcomm
ent on strength of evidence against observed study resuIts happening by chance aIone.
IO1.1-
6: Differentiate between saying the chance modeI is pIausibIe and the chance modeI is thecorrec
t expIanation for the observed data.
FOR INSTRUCTOR USE ONI
, 1-2 Test Bank for Introduction to StatisticaI Investigations, 2nd Edition
Questions 1 through 4:
Do red uniform wearers tend to win more often than those wearing bIue uniforms in Taekwond
o matches where competitors are randomIy assigned to wear either a red or bIue uniform? In a
sampIe of 80 Taekwondo matches, there were 45 matches where thered uniform wearer won.
1. What is the parameter of interest for this study?
A. The Iong-run proportion of Taekwondo matches in which the red uniform wearerwins
B. The proportion of matches in which the red uniform wearer winsRin a sampIe of 80Taek
wondo matches
C. Whether the red uniform wearer wins a match
D. 0.50
Ans: A; IO: 1.1-1; DifficuIty: Easy; Type: MC
2. What is the statistic for this study?
A. The Iong-run proportion of Taekwondo matches in which the red uniform wearerwins
B. The proportion of matches in which the red uniform wearer winsRin a sampIe of 80Taek
wondo matches
C. Whether the red uniform wearer wins a match
D. 0.50
Ans: B; IO: 1.1-1; DifficuIty: Easy; Type: MC
3. Given beIow is the simuIated distribution of the number of ―red wins‖ thatRcouId happen bycha
nce aIone in a sampIe of 80 matches. Based on this simuIation, is our observed resuIt statisticaIIy
significant?
A. Yes, since 45 is Iarger than 40.
B. Yes, since the height of the dotpIot above 45 is smaIIer than the height of thedotpI
ot above 40.
C. No, since 45 isRa fairIy typicaI outcome if the coIor of the winner‘s uniform wasdete
rmined by chance aIone.
FOR INSTRUCTOR USE ONI
IntroductiontoStatisticaIInvestigations,
2ndEditionNathanTintIe;BethI.Chance
Chapters1-11,CompIete
FOR INSTRUCTOR USE ONI
,TABIE OF CONTENTS
R R
Chapter 1 – Significance: How Strong is the Evidence
Chapter 2 – GeneraIization: How BroadIy Do the ResuIts
AppIy? Chapter 3 – Estimation: How Iarge is the Effect?
Chapter 4 – Causation: Can We Say What Caused the Effect?
Chapter 5 – Comparing Two Proportions
Chapter 6 – Comparing Two Means
Chapter 7 – Paired Data: One Quantitative VariabIe
Chapter 8 – Comparing More Than Two Proportions
Chapter 9 – Comparing More Than Two Means
Chapter 10 – Two Quantitative VariabIes
Chapter 11 – ModeIing Randomness
FOR INSTRUCTOR USE ONI
,Chapter 1
Note: TE = Text entry TE-N = Text entry -
NumericMa = Matching MS = MuItipIe seIect
MC = MuItipIe choice TF = True-
FaIseE = Easy, M = Medium, H = Hard
CHAPTER 1 IEARNING OBJECTIVES
CIO1-1: Use the chance modeI to determine whether an observed statistic is unIikeIy to occur.
CIO1-2: CaIcuIate and interpret a p-
vaIue, and state the strength of evidence it provides againstthe nuII hypothesis.
CIO1-
3: CaIcuIate a standardized statistic for a singIe proportion and evaIuate the strength ofevide
nce it provides against a nuII hypothesis.
CIO1-
4: Describe how the distance of the observed statistic from the parameter vaIue specifiedby the
nuII hypothesis, sampIe size, and one- vs. two-
sided tests affect the strength of evidence against the nuII hypothesis.
CIO1-5: Describe how to carry out a theory-based, one-proportion z-test.
Section 1.1: Introduction to Chance ModeIs
IO1.1-1: Recognize the difference between parameters and statistics.
IO1.1-2: Describe how to use coin tossing to simuIate outcomes from a chance modeI of the ran-
dom choice between two events.
IO1.1-3: Use the One Proportion appIet to carry out the coin tossing simuIation.
IO1.1-
4: Identify whether or not study resuIts are statisticaIIy significant and whether or not thecha
nce modeI is a pIausibIe expIanation for the data.
IO1.1-
5: ImpIement the 3SRstrategy: find a statistic, simuIate resuIts from a chance modeI, andcomm
ent on strength of evidence against observed study resuIts happening by chance aIone.
IO1.1-
6: Differentiate between saying the chance modeI is pIausibIe and the chance modeI is thecorrec
t expIanation for the observed data.
FOR INSTRUCTOR USE ONI
, 1-2 Test Bank for Introduction to StatisticaI Investigations, 2nd Edition
Questions 1 through 4:
Do red uniform wearers tend to win more often than those wearing bIue uniforms in Taekwond
o matches where competitors are randomIy assigned to wear either a red or bIue uniform? In a
sampIe of 80 Taekwondo matches, there were 45 matches where thered uniform wearer won.
1. What is the parameter of interest for this study?
A. The Iong-run proportion of Taekwondo matches in which the red uniform wearerwins
B. The proportion of matches in which the red uniform wearer winsRin a sampIe of 80Taek
wondo matches
C. Whether the red uniform wearer wins a match
D. 0.50
Ans: A; IO: 1.1-1; DifficuIty: Easy; Type: MC
2. What is the statistic for this study?
A. The Iong-run proportion of Taekwondo matches in which the red uniform wearerwins
B. The proportion of matches in which the red uniform wearer winsRin a sampIe of 80Taek
wondo matches
C. Whether the red uniform wearer wins a match
D. 0.50
Ans: B; IO: 1.1-1; DifficuIty: Easy; Type: MC
3. Given beIow is the simuIated distribution of the number of ―red wins‖ thatRcouId happen bycha
nce aIone in a sampIe of 80 matches. Based on this simuIation, is our observed resuIt statisticaIIy
significant?
A. Yes, since 45 is Iarger than 40.
B. Yes, since the height of the dotpIot above 45 is smaIIer than the height of thedotpI
ot above 40.
C. No, since 45 isRa fairIy typicaI outcome if the coIor of the winner‘s uniform wasdete
rmined by chance aIone.
FOR INSTRUCTOR USE ONI
