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TEST BANK
Introduction to Statistical Investigations,
2nd Edition Nathan Tintle; Beth L. Chance Chapters 1
- 11, Complete
TABLE OF CONTENTS
Chapter 1 – Significance: How Strong is the Evidence
Chapter 2 – Generalization: How Broadly Do the
Results Apply?
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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
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Chapter 1
Note: TE = Text entry TE-N =
Text entry - Numeric Ma =
Matching MS = Multiple
select
MC = Multiple choice TF =
True-False E = 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 specified by the
null hypothesis, sample size, and one- vs. two-sided
tests affect the strength of evidence against the null
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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.
https://www.stuvia.com/user/papersprime
FOR INSTRUCTOR USE ONLY
TEST BANK
Introduction to Statistical Investigations,
2nd Edition Nathan Tintle; Beth L. Chance Chapters 1
- 11, Complete
TABLE OF CONTENTS
Chapter 1 – Significance: How Strong is the Evidence
Chapter 2 – Generalization: How Broadly Do the
Results Apply?
https://www.stuvia.com/user/papersprime
FOR INSTRUCTOR USE ONLY
,https://www.stuvia.com/user/papersprimehttps://www.stuvia.com/user/papersprime
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
https://www.stuvia.com/user/papersprime
FOR INSTRUCTOR USE ONLY
,https://www.stuvia.com/user/papersprimehttps://www.stuvia.com/user/papersprime
Chapter 1
Note: TE = Text entry TE-N =
Text entry - Numeric Ma =
Matching MS = Multiple
select
MC = Multiple choice TF =
True-False E = 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 specified by the
null hypothesis, sample size, and one- vs. two-sided
tests affect the strength of evidence against the null
https://www.stuvia.com/user/papersprime
FOR INSTRUCTOR USE ONLY
, https://www.stuvia.com/user/papersprimehttps://www.stuvia.com/user/papersprime
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.
https://www.stuvia.com/user/papersprime
FOR INSTRUCTOR USE ONLY
