TEST BANK
Introduction to Statistical Investigations,
2nd Edition Nathan Tintle; Beth L. Chance
Chapters 1 - 11, Complete
FOR INSTRUCTOR USE ONLY
,TABLE OF CONTENTS
Chapter 1 – Significance: How Strong is the Evidence
Chapter 2 – Generalization: How Broadly Do the Results Apply?
Chapter 3 – Estimation: How Large 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 Variable
Chapter 8 – Comparing More Than Two Proportions
Chapter 9 – Comparing More Than Two Means
Chapter 10 – Two Quantitative Variables
Chapter 11 – Modeling Randomness
FOR INSTRUCTOR USE ONLY
,Chapter 1
Note: TE = Text entry TE-N = Text entry - NumericMa
= Matching MS = Multiple select
MC = Multiple choice TF = True-FalseE =
Easy, M = Medium, H = Hard
CHAPTER 1 LEARNING OBJECTIVES
CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
CLO1-2: Calculate and interpret a p-value, and state the strength of evidence it provides againstthe null
hypothesis.
CLO1-3: Calculate a standardized statistic for a single proportion and evaluate the strength of
evidence it provides against a null hypothesis.
CLO1-4: Describe how the distance of the observed statistic from the parameter value specifiedby the
null hypothesis, sample size, and one- vs. two-sided tests affect the strength of evidence against
the null hypothesis.
CLO1-5: Describe how to carry out a theory-based, one-proportion z-test.
Section 1.1: Introduction to Chance Models
LO1.1-1: Recognize the difference between parameters and statistics.
LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-dom
choice between two events.
LO1.1-3: Use the One Proportion applet to carry out the coin tossing simulation.
LO1.1-4: Identify whether or not study results are statistically significant and whether or not the
chance model is a plausible explanation for the data.
LO1.1-5: Implement the 3S strategy: find a statistic, simulate results from a chance model, and
comment on strength of evidence against observed study results happening by chance alone.
LO1.1-6: Differentiate between saying the chance model is plausible and the chance model is the correct
explanation for the observed data.
FOR INSTRUCTOR USE ONLY
, 1-2 Test Bank for Introduction to Statistical Investigations, 2nd Edition
Questions 1 through 4:
Do red duniform dwearers dtend dto dwin dmore doften dthan dthose dwearing dblue duniforms din
dTaekwondo dmatches dwhere dcompetitors dare drandomly dassigned dto dwear deither da dred
dor dblue duniform? dIn da dsample dof d80 dTaekwondo dmatches, dthere dwere d45 dmatches
dwhere dthedred duniform dwearer dwon.
1. What dis dthe dparameter dof dinterest dfor dthis dstudy?
A. The dlong-run dproportion dof dTaekwondo dmatches din dwhich dthe dred duniform
dwearerdwins
B. The dproportion dof dmatches din dwhich dthe dred duniform dwearer dwins din da dsample
dof d80dTaekwondo dmatches
C. Whether dthe dred duniform dwearer dwins da dmatch
D. d 0.50
Ans: dA; dLO: d1.1-1; dDifficulty: dEasy; dType: dMC
2. What dis dthe dstatistic dfor dthis dstudy?
A. The dlong-run dproportion dof dTaekwondo dmatches din dwhich dthe dred duniform
dwearerdwins
B. The dproportion dof dmatches din dwhich dthe dred duniform dwearer dwins din da dsample
dof d80dTaekwondo dmatches
C. Whether dthe dred duniform dwearer dwins da dmatch
D. d 0.50
Ans: dB; dLO: d1.1-1; dDifficulty: dEasy; dType: dMC
3. Given dbelow dis dthe dsimulated ddistribution dof dthe dnumber dof d―red dwins‖ dthat dcould
dhappen dby dchance dalone din da dsample dof d80 dmatches. dBased don dthis dsimulation, dis dour
dobserved dresult dstatistically dsignificant?
A. Yes, dsince d45 dis dlarger dthan d40.
B. Yes, dsince dthe dheight dof dthe ddotplot dabove d45 dis dsmaller dthan dthe dheight
dof dtheddotplot dabove d40.
C. No, dsince d45 dis da dfairly dtypical doutcome dif dthe dcolor dof dthe dwinner‘s
FOR INSTRUCTOR USE ONLY
Introduction to Statistical Investigations,
2nd Edition Nathan Tintle; Beth L. Chance
Chapters 1 - 11, Complete
FOR INSTRUCTOR USE ONLY
,TABLE OF CONTENTS
Chapter 1 – Significance: How Strong is the Evidence
Chapter 2 – Generalization: How Broadly Do the Results Apply?
Chapter 3 – Estimation: How Large 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 Variable
Chapter 8 – Comparing More Than Two Proportions
Chapter 9 – Comparing More Than Two Means
Chapter 10 – Two Quantitative Variables
Chapter 11 – Modeling Randomness
FOR INSTRUCTOR USE ONLY
,Chapter 1
Note: TE = Text entry TE-N = Text entry - NumericMa
= Matching MS = Multiple select
MC = Multiple choice TF = True-FalseE =
Easy, M = Medium, H = Hard
CHAPTER 1 LEARNING OBJECTIVES
CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
CLO1-2: Calculate and interpret a p-value, and state the strength of evidence it provides againstthe null
hypothesis.
CLO1-3: Calculate a standardized statistic for a single proportion and evaluate the strength of
evidence it provides against a null hypothesis.
CLO1-4: Describe how the distance of the observed statistic from the parameter value specifiedby the
null hypothesis, sample size, and one- vs. two-sided tests affect the strength of evidence against
the null hypothesis.
CLO1-5: Describe how to carry out a theory-based, one-proportion z-test.
Section 1.1: Introduction to Chance Models
LO1.1-1: Recognize the difference between parameters and statistics.
LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-dom
choice between two events.
LO1.1-3: Use the One Proportion applet to carry out the coin tossing simulation.
LO1.1-4: Identify whether or not study results are statistically significant and whether or not the
chance model is a plausible explanation for the data.
LO1.1-5: Implement the 3S strategy: find a statistic, simulate results from a chance model, and
comment on strength of evidence against observed study results happening by chance alone.
LO1.1-6: Differentiate between saying the chance model is plausible and the chance model is the correct
explanation for the observed data.
FOR INSTRUCTOR USE ONLY
, 1-2 Test Bank for Introduction to Statistical Investigations, 2nd Edition
Questions 1 through 4:
Do red duniform dwearers dtend dto dwin dmore doften dthan dthose dwearing dblue duniforms din
dTaekwondo dmatches dwhere dcompetitors dare drandomly dassigned dto dwear deither da dred
dor dblue duniform? dIn da dsample dof d80 dTaekwondo dmatches, dthere dwere d45 dmatches
dwhere dthedred duniform dwearer dwon.
1. What dis dthe dparameter dof dinterest dfor dthis dstudy?
A. The dlong-run dproportion dof dTaekwondo dmatches din dwhich dthe dred duniform
dwearerdwins
B. The dproportion dof dmatches din dwhich dthe dred duniform dwearer dwins din da dsample
dof d80dTaekwondo dmatches
C. Whether dthe dred duniform dwearer dwins da dmatch
D. d 0.50
Ans: dA; dLO: d1.1-1; dDifficulty: dEasy; dType: dMC
2. What dis dthe dstatistic dfor dthis dstudy?
A. The dlong-run dproportion dof dTaekwondo dmatches din dwhich dthe dred duniform
dwearerdwins
B. The dproportion dof dmatches din dwhich dthe dred duniform dwearer dwins din da dsample
dof d80dTaekwondo dmatches
C. Whether dthe dred duniform dwearer dwins da dmatch
D. d 0.50
Ans: dB; dLO: d1.1-1; dDifficulty: dEasy; dType: dMC
3. Given dbelow dis dthe dsimulated ddistribution dof dthe dnumber dof d―red dwins‖ dthat dcould
dhappen dby dchance dalone din da dsample dof d80 dmatches. dBased don dthis dsimulation, dis dour
dobserved dresult dstatistically dsignificant?
A. Yes, dsince d45 dis dlarger dthan d40.
B. Yes, dsince dthe dheight dof dthe ddotplot dabove d45 dis dsmaller dthan dthe dheight
dof dtheddotplot dabove d40.
C. No, dsince d45 dis da dfairly dtypical doutcome dif dthe dcolor dof dthe dwinner‘s
FOR INSTRUCTOR USE ONLY
