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

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IntroductiontoStatisticalInvestigations,
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nd
EditionNathanTintle;Beth Chance f




n Chapters 1-11,Complete
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Chapter1–Significance:HowStrongistheEvidence
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Chapter2–Generalization:HowBroadlyDotheResultsApply?Chapter

3–Estimation:HowLargeistheEffect?
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Chapter4–Causation:CanWeSayWhatCausedtheEffect?Chapter5–
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ComparingTwoProportions

Chapter6–ComparingTwoMeans
Chapter7–PairedData:OneQuantitativeVariableChapter8–
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ComparingMoreThanTwoProportionsChapter9– f




ComparingMoreThanTwoMeansChapter10– f




TwoQuantitativeVariables

Chapter11–ModelingRandomness




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,Chapter 1 f




Note: TE = Textentry f f TE-N=Textentry-
NumericMa = Matching
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MC = Multiplechoice
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FalseE = Easy, M = Medium, H = Hard f f f f f f f f




CHAPTER1LEARNINGOBJECTIVES f f




CLO1-1: Use thechance modeltodetermine whetheranobserved statisticis unlikely tooccur.
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CLO1-2:Calculateandinterpretap-
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value,andstate the strength of evidence it provides againstthe null hypothesis.
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CLO1-
3:Calculateastandardizedstatistic forasingleproportionandevaluatethe strengthofev idence n f f f




itprovidesagainstanullhypothesis.
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CLO1-
4: Describe how the distance of the observed statistic from the parameter value specifiedby the
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nullhypothesis, samplesize,andone-vs.two-
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sidedtests affect the strength of evidence against the null hypothesis.
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CLO1-5:Describe howto carry out atheory-based,one-proportion z-test.
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Section1.1:IntroductiontoChanceModels
LO1.1-1:Recognizethedifferencebetweenparametersandstatistics.
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LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-dom choice
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between two events. f f f




LO1.1-3:UsetheOneProportionapplettocarryoutthecointossingsimulation. n




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4:Identify whether or notstudy results are statistically significant and whether or not thec hance
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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, andco mmenton
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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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explanationfor theobserveddata.
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, 1-2 TestBankfor IntroductiontoStatisticalInvestigations,2ndEdition
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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 Taekw ondo
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matches where competitors are randomly assigned to wear either a red or blue unifor m? In a
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sampleof80Taekwondomatches,therewere45matcheswherethereduniformwearerwon.
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1. What is the parameterof interest forthis study?
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A. The long- f




runproportion 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 80T
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aekwondo matches f f




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




D. 0.50
Ans: A;LO: 1.1-1; Difficulty: Easy; Type:MC
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2. What is the statisticforthis study?
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A. The long- f




runproportion 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 80T
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aekwondo matches f f




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




D. 0.50
Ans:B;LO: 1.1-1; Difficulty:Easy; Type:MC
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3. Givenbelow is the simulated distribution of the number of ―redwins‖that could happen by chance alone
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in a sample of 80 matches. Based on this simulation, is our observed result stat istically significant?
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A. Yes, since 45 is larger than 40. f f f f f f




B. Yes, since the height of the dotplot above 45 is smaller than the height of thed
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otplotabove40. f




C. No, since 45 is a fairly typical outcome if the color of the winner‘s uniform wasd
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