Introduction to Statistical Investigations, 2nd Edition TEST BANK by Nathan Tintle; Beth L. Chance, Verified Chapters 1 - 11, Complete Newest Version

TEST BANK

Introduction to Statistical Investigations,

2nd Edition Nathan Tintle; Beth L.

Chance Chapters 1 - 11, Complete




FOR INSTRUCTOR USE ONLY
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,TABLE OF CONTENTS
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Chapter 1 – Significance: How Strong is the Evidence
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Chapter 2 – NW NW




Generalization: How Broadly Do the Results Apply?
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Chapter 3 – Estimation: How Large is the Effect?
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Chapter 4 – Causation: Can We Say What Caused the Effect?
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Chapter 5 – Comparing Two Proportions
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Chapter 6 – Comparing Two Means
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Chapter 7 – Paired Data: One Quantitative Variable
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Chapter 8 – Comparing More Than Two Proportions
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Chapter 9 – Comparing More Than Two Means
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Chapter 10 – Two Quantitative Variables
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FOR INSTRUCTOR USE ONLY
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,Chapter 11 – Modeling Randomness
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FOR INSTRUCTOR USE ONLY
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, Chapter 1 N W




Note: TE =
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NW NumericMa = Matching W
N N W N W MS = Multiple select
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MC = Multiple choice N W N W NW TF = True-NW NW




FalseE = Easy, M = Medium, H = Hard
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CHAPTER 1 LEARNING OBJECTIVES NW NW NW




CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
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CLO1-2: Calculate and interpret a p-
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value, and state the strength of evidence it provides againstthe null hypothesis.
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CLO1-
3: Calculate a standardized statistic for a single proportion and evaluate the strength o
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fevidence it provides against a null hypothesis.
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CLO1-
4: Describe how the distance of the observed statistic from the parameter value specifiedb
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y the null hypothesis, sample size, and one- vs. two-
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sided tests affect the strength of evidence against the null hypothesis.
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CLO1-5: Describe how to carry out a theory-based, one-proportion z-test.
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Section 1.1: Introduction to Chance Models NW NW NW NW NW




LO1.1-1: Recognize the difference between parameters and statistics.
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LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-
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FOR INSTRUCTOR USE ONLY NW NW NW