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Introduction to Statistical Investigations, 2nd Edition TEST BANK by Nathan Tintle; Beth L. Chance, Verified Chapters 1 - 11, Complete Newest Version$18.99
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TEST BANK For Introduction to Statistical Investigations, 2nd Edition by Nathan Tintle; Beth L. Chance, Verified Chapters 1 - 11, Complete Newest Version TEST BANK For Introduction to Statistical Investigations, 2nd Edition by Nathan Tintle; Beth L. Chance, Verified Chapters 1 - 11, Complete Newest...
Note: TE = Text entry
lklklk l k l k lk TE-N = Text entry - lk lk lk lk
NumericMa = Matching
lk kl l k l k MS = Multiple selectl k lk lk
MC = Multiple choice l k l k lk TF = True- lk lk
FalseE = Easy, M = Medium, H = Hard
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CHAPTER 1 LEARNING OBJECTIVES lk lk lk
CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
lk lk lk lk lk lk lk lk lk lk lk lk lk lk
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 ofeviden
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ce 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 nu
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ll 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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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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dom 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 thechanc
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e 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, andcomme
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nt on strength of evidence against observed study results happening by chance alone.
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LO1.1-
6: Differentiate between saying the chance model is plausible and the chance model is thecorrect
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explanation for the observed data. lk lk lk lk
FOR INSTRUCTOR USE ONLY lk lk lk
, 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 Taekwondo
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matches where competitors are randomly assigned to wear either a red or blue uniform? In a sa
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mple of 80 Taekwondo matches, there were 45 matches where thered 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 wearerwins
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B. The proportion of matches in which the red uniform wearer wins in a sample of 80Taekw
lk lk lk lk lk lk lk lk lk lk lk lk lk lk lk kl
ondo matches lk
C. Whether the red uniform wearer wins a match lk lk lk lk lk lk lk
3. Given below is the simulated distribution of the number of ―red wins‖ that could happen bychance
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alone in a sample of 80 matches. Based on this simulation, is our observed result statistically signif
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icant?
A. Yes, since 45 is larger than 40. lk lk lk lk lk lk
B. Yes, since the height of the dotplot above 45 is smaller than the height of thedotplot
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above 40. lk
C. No, since 45 is a fairly typical outcome if the color of the winner‘s uniform wasdeterm
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ined by chance alone. lk lk lk
FOR INSTRUCTOR USE ONLY lk lk lk
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