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Exam (elaborations)

Introduction to Statistical Investigations – 2nd Edition by Nathan Tintle & Beth L. Chance | Test Bank Chapters 1–11 Complete

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This document provides the complete test bank for Introduction to Statistical Investigations (2nd Edition) by Nathan Tintle and Beth L. Chance, covering Chapters 1 through 11. It includes multiple-choice questions, true/false statements, and problem-based exercises with solutions. The material is comprehensive and aligned with the core topics of the textbook, making it a valuable resource for both exam preparation and teaching support.

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Introduction to Statistics
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Uploaded on
October 1, 2025
Number of pages
326
Written in
2025/2026
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TEST BANK
Introduction to Statistical Investigations,

2nd Edition Nathan Tintle; Beth L. Chance
Chapters 1 - 11, Complete




sg




T
A
B
LE s




g O
F sg




CONTENTS sg




FOR INSTRUCTOR USE ONLY
sg sg sg

,Chapter 1 – Significance: How Strong is the Evidence
sg sg sg sg sg sg sg sg sg




Chapter 2 – Generalization: How Broadly Do the Results Apply?
sg sg sg sg sg sg sg sg sg sg




Chapter 3 – Estimation: How Large is the Effect?
sg sg sg sg sg sg sg sg sg




Chapter 4 – Causation: Can We Say What Caused the Effect?
sg sg sg sg sg sg sg sg sg sg sg




Chapter 5 – Comparing Two Proportions
sg sg sg sg sg sg




Chapter 6 – Comparing Two Means
sg sg sg sg sg sg




Chapter 7 – Paired Data: One Quantitative Variable
sg sg sg sg sg sg sg sg




Chapter 8 – Comparing More Than Two Proportions
sg sg sg sg sg sg sg sg




Chapter 9 – Comparing More Than Two Means
sg sg sg sg sg sg sg sg




Chapter 10 – Two Quantitative Variables
sg sg sg sg sg sg




Chapter 11 – Modeling Randomness
sg sg sg sg




FOR INSTRUCTOR USE ONLY
sg sg sg

,Chapter 1 s g




Note: TE = Text entry
sgsgsg s g s g sg TE-N = Text entry - sg sg sg sg




sg NumericMa = Matching sg s g s g MS = Multiple select
s g sg sg




MC = Multiple choice s g s g sg TF = True- sg sg




FalseE = Easy, M = Medium, H = Hard
sg sg sg sg sg sg sg sg sg




CHAPTER 1 LEARNING OBJECTIVES sg sg sg




CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
sg sg sg sg sg sg sg sg sg sg sg sg sg sg




CLO1-2: Calculate and interpret a p-
sg sg sg sg sg



value, and state the strength of evidence it provides againstthe null hypothesis.
sg sg sg sg sg sg sg sg sg sg sg sg




CLO1-
3: Calculate a standardized statistic for a single proportion and evaluate the strength ofevide
sg sg sg sg sg sg sg sg sg sg sg sg sg sg



nce it provides against a null hypothesis.
sg sg sg sg sg sg




CLO1-
4: Describe how the distance of the observed statistic from the parameter value specifiedby the
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



null hypothesis, sample size, and one- vs. two-
sg sg sg sg sg sg sg



sided tests affect the strength of evidence against the null hypothesis.
sg sg sg sg sg sg sg sg sg sg




CLO1-5: Describe how to carry out a theory-based, one-proportion z-test.
sg sg sg sg sg sg sg sg sg




Section 1.1: Introduction to Chance Models sg sg sg sg sg




LO1.1-1: Recognize the difference between parameters and statistics.
sg sg sg sg sg sg sg




LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



dom choice between two events.
sg sg sg sg sg




LO1.1-3: Use the One Proportion applet to carry out the coin tossing simulation.
sg sg sg sg sg sg sg sg sg sg sg sg




LO1.1-
4: Identify whether or not study results are statistically significant and whether or not thechan
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



ce model is a plausible explanation for the data.
sg sg sg sg sg sg sg sg




LO1.1-
5: Implement the 3S strategy: find a statistic, simulate results from a chance model, andcomm
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



ent on strength of evidence against observed study results happening by chance alone.
sg sg sg sg sg sg sg sg sg sg sg sg




LO1.1-
6: Differentiate between saying the chance model is plausible and the chance model is thecorrec
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



t explanation for the observed data.
sg sg sg sg sg




FOR INSTRUCTOR USE ONLY sg sg sg

, 1-2 Test Bank for Introduction to Statistical Investigations, 2nd Edition
sg sg sg sg sg sg sg sg




Questions 1 through 4:
sg sg sg




Do red uniform wearers tend to win more often than those wearing blue uniforms in Taekwond
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



o matches where competitors are randomly assigned to wear either a red or blue uniform? In a
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



sample of 80 Taekwondo matches, there were 45 matches where thered uniform wearer won.
sg sg sg sg sg sg sg sg sg sg sg sg sg sg




1. What is the parameter of interest for this study?
sg sg sg sg sg sg sg sg




A. The long-run proportion of Taekwondo matches in which the red uniform wearerwins
sg sg sg sg sg sg sg sg sg sg sg sg




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



wondo matches sg




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




D. 0.50 sg




Ans: A; LO: 1.1-1; Difficulty: Easy; Type: MC
sg sg sg sg sg sg sg




2. What is the statistic for this study?
sg sg sg sg sg sg




A. The long-run proportion of Taekwondo matches in which the red uniform wearerwins
sg sg sg sg sg sg sg sg sg sg sg sg




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



wondo matches sg




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




D. 0.50 sg




Ans: B; LO: 1.1-1; Difficulty: Easy; Type: MC
sg sg sg sg sg sg sg




3. Given below is the simulated distribution of the number of ―red wins‖ that could happen bychan
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



ce alone in a sample of 80 matches. Based on this simulation, is our observed result statistically s
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



ignificant?




A. Yes, since 45 is larger than 40. sg sg sg sg sg sg




B. Yes, since the height of the dotplot above 45 is smaller than the height of thedotpl
sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg sg



ot above 40. sg sg




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



mined by chance alone. sg sg sg




FOR INSTRUCTOR USE ONLY sg sg sg

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