TEST BANK
Introduction to Statistical
Investigations,
2nd Edition Nathan Tintle; Beth L. Chance
Chapters 1 - 11, Complete
FOR INSTRUCTOR USE ONLY
,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 = Teẋt entry TE-N = Teẋt entry - Numeric
Ma = 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 against
the 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
thechance model is a plausible eẋplanation 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 eẋplanation for the observed data.
FOR INSTRUCTOR USE ONLY
Introduction to Statistical
Investigations,
2nd Edition Nathan Tintle; Beth L. Chance
Chapters 1 - 11, Complete
FOR INSTRUCTOR USE ONLY
,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 = Teẋt entry TE-N = Teẋt entry - Numeric
Ma = 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 against
the 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
thechance model is a plausible eẋplanation 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 eẋplanation for the observed data.
FOR INSTRUCTOR USE ONLY
