Test bank For Introduction to Statistical Investigations, 2nd Edition by Nathan Tintle; Beth L. Chance, Complete Chapters 1 - 11, Verified Latest Version With correct Answers 2025 newest

TESTBANKn n




Introduction to Statistical Investigations,
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2nd Edition Nathan Tintle; Beth L. Chance
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Chapters 1-11,Complete
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Chapter1–Significance:HowStrongistheEvidence
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Chapter2–Generalization:HowBroadlyDotheResultsApply? Chapter
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3 – Estimation: How Large is the Effect?
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Chapter4–Causation:CanWeSayWhatCausedtheEffect? Chapter
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5 – Comparing Two Proportions
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Chapter6–ComparingTwoMeans
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Chapter 7– Paired Data: One Quantitative Variable
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Chapter8–ComparingMoreThanTwoProportions
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Chapter 9 – Comparing More Than Two Means Chapter 10
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– Two Quantitative Variables
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Chapter11–ModelingRandomness
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,Chapter 1 n




Note: TE = Text entry n n n TE-N = Text entry - n n n n




NumericMa = Matching
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MC = Multiple choice
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FalseE = Easy, M = Medium, H = Hard n n n n n n n n n




CHAPTER 1 LEARNING OBJECTIVES n n n




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 ofev
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nidence it provides against a null hypothesis. n n n n n n




CLO1-
4: Describe how the distance of the observed statistic from the parameter value specifiedby t he
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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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Section1.1:IntroductiontoChanceModels n n n n n




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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n LO1.1-
4: Identify whether or not study results are statistically significant and whether or not thec
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hance model is a plausible explanation for the data. n n n n n n n n




LO1.1-
5: Implement the 3S strategy: find a statistic, simulate results from a chance model, andco
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mment 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 thecor rect
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explanation for the observed data.
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, 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 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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sample of 80 Taekwondo matches, there were 45 matches where thered uniform w earer won.
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1. What is the parameter of interest for this study?
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A. The long- n




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 80T
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aekwondo matches n n




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




D. 0.50
Ans: A; LO: 1.1-1; Difficulty: Easy; Type: MC
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2. What is the statistic for this study?
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A. The long- n




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 80T
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aekwondo matches n n




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




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




B. Yes, since the height of the dotplot above 45 is smaller than the height of thed
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otplot above 40. n n n




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