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Test bank For Introduction to Statistical Investigations, 2nd Edition by Nathan Tintle; Beth L. Chance, Complete Chapters 1 - 11, Verified Latest Version

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Preview 4 out of 300 pages

Test bank For Introduction to Statistical Investigations, 2nd Edition by Nathan Tintle; Beth L. Chance, Complete Chapters 1 - 11, Verified Latest Version

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TEST BANK gh gh




Introduction to Statistical Investigations,
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nd
2 Edition Nathan Tintle; Beth L. Chance
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Chapters 1 - 11, Complete
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FOR INSTRUCTOR USE
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ONLY

,TABLE OF CONTENTS
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Chapter 1 – Significance: How Strong is the Evidence
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Chapter 2 – 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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Chapter 11 – Modeling Randomness
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FOR INSTRUCTOR USE
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ONLY

,Chapter 1 g h




Note: gh gh gh TE = g h g h Text entry gh TE-N = Text entry - gh gh gh gh




gh NumericMa = gh g h g h Matching MS = Multiple select
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MC = g h g h Multiple choice gh TF = True-FalseE
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gh = Easy, M = Medium, H = Hard
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CHAPTER 1 LEARNING OBJECTIVES gh gh gh




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-value, and state the strength of evidence it provides againstthe
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null hypothesis.
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CLO1-3: Calculate a standardized statistic for a single proportion and evaluate the strength
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ofevidence it provides against a null hypothesis.
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CLO1-4: Describe how the distance of the observed statistic from the parameter value specifiedby the
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null hypothesis, sample size, and one- vs. two-sided tests affect the strength of evidence
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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 gh gh gh gh gh




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-dom
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choice between two events.
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LO1.1-3: Use the One Proportion applet to carry out the coin tossing simulation.
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LO1.1-4: Identify whether or not study results are statistically significant and whether or not
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thechance model is a plausible explanation for the data.
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LO1.1-5: Implement the 3S strategy: find a statistic, simulate results from a chance model,
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andcomment on strength of evidence against observed study results happening by chance
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alone. gh




LO1.1-6: Differentiate between saying the chance model is plausible and the chance model is
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thecorrect explanation for the observed data.
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FOR INSTRUCTOR USE gh gh



ONLY

, 1-2 Test Bank for Introduction to Statistical Investigations, 2nd Edition
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Questions 1 through 4:
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Do red uniform wearers tend to win more often than those wearing blue uniforms in
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Taekwondo matches where competitors are randomly assigned to wear either a red or blue
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uniform? In a sample of 80 Taekwondo matches, there were 45 matches where thered
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uniform wearer won.
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1. What is the parameter of interest for this study?
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A. The long-run proportion of Taekwondo matches in which the red uniform
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wearerwins gh gh




B. The proportion of matches in which the red uniform wearer wins in a sample of
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80Taekwondo matches gh gh gh




C. Whether the red uniform wearer wins a match gh gh gh gh gh gh gh




D. 0.50 gh




2. What is the statistic for this study?
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A. The long-run proportion of Taekwondo matches in which the red uniform
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wearerwins gh gh




B. The proportion of matches in which the red uniform wearer wins in a sample of
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80Taekwondo matches gh gh gh




C. Whether the red uniform wearer wins a match gh gh gh gh gh gh gh




D. 0.50 gh




3. Given below is the simulated distribution of the number of ―red wins‖ that could happen
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by chance alone in a sample of 80 matches. Based on this simulation, is our observed result
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statistically significant?
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A. Yes, since 45 is larger than 40.gh gh gh gh gh gh




B. Yes, since the height of the dotplot above 45 is smaller than the height of
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thedotplot above 40.gh gh gh gh




C. No, since 45 is a fairly typical outcome if the color of the winner‘s uniform
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wasdetermined by chance alone.
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FOR INSTRUCTOR USE gh gh



ONLY

Connected book
 image
Nathan Tintle, Beth L. Chance, George W. Cobb, Allan J. Rossman, Soma Roy, Todd Swanson, Jill VanderStoep Introduction to Statistical Investigations
Publisher: 2020 ISBN: 9781119683452 Edition: Unknown

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