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“Test Bank for Introduction to Statistical Investigations 2nd Edition by Nathan Tintle, Beth L. Chance & George W. Cobb – Latest 2025/2026 Update”

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“Get exam-ready with the Test Bank for Introduction to Statistical Investigations, 2nd Edition by Nathan Tintle, Beth L. Chance & George W. Cobb – Updated for 2025/2026. This test bank provides hundreds of multiple-choice, true/false, and problem-solving questions that align directly with the textbook, giving students the tools they need to succeed. Latest 2025/2026 update Comprehensive coverage of descriptive statistics, probability, sampling, inference, hypothesis testing, regression, and experimental design Verified answers for accurate exam prep Perfect for statistics, data science, business, and social science students Ideal for quizzes, midterms, finals, and assignments Ace your statistics course with this complete and reliable test bank.”

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Introduction To Statistical Investigations
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Introduction to Statistical Investigations
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Introduction to Statistical Investigations

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Subido en
4 de octubre de 2025
Número de páginas
332
Escrito en
2025/2026
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Examen
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TEST BANK
Introduction to Statistical Investigations,
2nd Edition Nathan Tintle; Beth L. Chance
Chapters 1 - 11, Complete




FOR INSTRUCTOR USE ONLY

,TABLE OF CONTENTS


Chapter 1 – Significance: How Strong is the Evidence

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

Chapter 3 – Estimation: How Large is the Effect?

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

Chapter 5 – Comparing Two Proportions

Chapter 6 – Comparing Two Means

Chapter 7 – Paired Data: One Quantitative Variable

Chapter 8 – Comparing More Than Two Proportions

Chapter 9 – Comparing More Than Two Means

Chapter 10 – Two Quantitative Variables

Chapter 11 – Modeling Randomness




FOR INSTRUCTOR USE ONLY

,Chapter 1 G




Note: TE =
GGG G G Text entry G TE-N = Text entry - NumericMa
G G G G G G




G = G Matching MS = Multiple select
G G G




MC = Multiple choice
G G G TF = True-FalseE =
G G G G




G Easy, M = Medium, H = Hard
G G G G G G




CHAPTER 1 LEARNING OBJECTIVES
G G G




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



CLO1-2: Calculate and interpret a p-value, and state the strength of evidence it provides againstthe
G G G G G G G G G G G G G G G


null hypothesis.
G G




CLO1-3: Calculate a standardized statistic for a single proportion and evaluate the strength of
G G G G G G G G G G G G G


evidence it provides against a null hypothesis.
G G G G G G G



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


null hypothesis, sample size, and one- vs. two-sided tests affect the strength of evidence
G G G G G G G G G G G G G G


against the null hypothesis.
G G G G



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




Section 1.1: Introduction to Chance Models G G G G G




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



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


choice between two events.
G G G G



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



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


chance model is a plausible explanation for the data.
G G G G G G G G G




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


comment on strength of evidence against observed study results happening by chance
G G G G G G G G G G G G


alone.
G



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


correct explanation for the observed data.
G G G G G G




FOR INSTRUCTOR USE ONLY

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




Questions 1 through 4:
G G G




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


Taekwondo matches where competitors are randomly assigned to wear either a red or blue
G G G G G G G G G G G G G G


uniform? In a sample of 80 Taekwondo matches, there were 45 matches where thered
G G G G G G G G G G G G G G G


uniform wearer won.
G G G



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



A. The long-run proportion of Taekwondo matches in which the red uniform wearer
G G G G G G G G G G G


wins G



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


Taekwondo matches
G G



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



D. 0.50 G



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



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




A. The long-run proportion of Taekwondo matches in which the red uniform wearer
G G G G G G G G G G G


wins G



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


Taekwondo matches
G G



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



D. 0.50 G



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




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


chance alone in a sample of 80 matches. Based on this simulation, is our observed result
G G G G G G G G G G G G G G G G


statistically significant?
G G




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



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


dotplot above 40.
G G G



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


FOR INSTRUCTOR USE ONLY
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