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TEST BANK for Introduction to Statistical Investigations, 2nd Edition Nathan Tintle; Beth L. Chance Chapters 1 - 11, Complete

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TEST BANK for Introduction to Statistical Investigations, 2nd Edition Nathan Tintle; Beth L. Chance Chapters 1 - 11, Complete TEST BANK for Introduction to Statistical Investigations, 2nd Edition Nathan Tintle; Beth L. Chance Chapters 1 - 11, Complete TEST BANK for Introduction to Statistical Investigations, 2nd Edition Nathan Tintle; Beth L. Chance Chapters 1 - 11, Complete TEST BANK for Introduction to Statistical Investigations, 2nd Edition Nathan Tintle; Beth L. Chance Chapters 1 - 11, Complete Test bank for Introduction to Statistical Investigations Introduction to Statistical Investigations 2nd Edition test bank Nathan Tintle test bank Beth L. Chance test bank Statistical Investigations 2nd Edition chapters Chapters 1-11 test bank Statistics test bank Introduction to Statistics exam resources Statistical Investigations college textbook Statistics textbook test bank Test bank chapter 1 Introduction to Statistics Test bank chapter 2 Statistical Reasoning Test bank chapter 3 Probability and Statistics Test bank chapter 4 Statistical Methods Test bank chapter 5 Data Analysis Test bank chapter 6 Experimental Design Test bank chapter 7 Statistical Models Test bank chapter 8 Regression Analysis Test bank chapter 9 Hypothesis Testing Test bank chapter 10 Confidence Intervals Test bank chapter 11 Statistical Software Statistical Investigations Nathan Tintle Statistical analysis educational resources Stats course test bank chapters 1-11 Study aids for Statistical Investigations Academic test bank statistical studies Introduction to statistics Nathan Tintle

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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
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,TABLE OF CONTENTS
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Chapter 1 – Significance: How Strong is the Evidence
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Chapter 2 –
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dGeneralization: How Broadly Do the Results Apply?
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Chapter 3 – Estimation: How Large is the Effect?
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Chapter 4 –
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dCausation: Can We Say What Caused the Effect?
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Chapter 5 – Comparing Two Proportions
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Chapter 6 – Comparing Two Means
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Chapter 7 – Paired Data: One Quantitative Variable
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Chapter 8 – Comparing More Than Two Proportions
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Chapter 9 – Comparing More Than Two Means
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Chapter 10 – Two Quantitative Variables
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Chapter 11 – Modeling Randomness
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FOR INSTRUCTOR USE ONLY
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,Chapter 1 d




Note: TE = Text entry
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d NumericMa = Matching d d d MS = Multiple select
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MC = Multiple choice
d d d TF = True-
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FalseE = Easy, M = Medium, H = Hard
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CHAPTER 1 LEARNING OBJECTIVES d d d




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 str
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ength ofevidence it provides against a null hypothesis.
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CLO1-
4: Describe how the distance of the observed statistic from the parameter value spe
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cifiedby the 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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Section 1.1: Introduction to Chance Models d d d d d




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 t
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he ran-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
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or not thechance 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 mo
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del, andcomment on strength of evidence against observed study results happen
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ing by chance alone.
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LO1.1-
6: Differentiate between saying the chance model is plausible and the chance mode
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l is thecorrect explanation for the observed data.
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FOR INSTRUCTOR USE ONLY d d d

, 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 i
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n Taekwondo matches where competitors are randomly assigned to wear either a
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red or blue uniform? In a sample of 80 Taekwondo matches, there were 45 matche
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s 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- d


run proportion of Taekwondo matches in which the red uniform wearerwi
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ns
B. The proportion of matches in which the red uniform wearer wins in a sampl
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e of 80Taekwondo matches
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C. Whether the red uniform wearer wins a match d d d d d d d



D. 0.50 d



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- d


run proportion of Taekwondo matches in which the red uniform wearerwi
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ns
B. The proportion of matches in which the red uniform wearer wins in a sampl
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e of 80Taekwondo matches
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C. Whether the red uniform wearer wins a match d d d d d d d



D. 0.50 d



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 ha
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ppen bychance alone in a sample of 80 matches. Based on this simulation, is our o
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bserved result statistically significant?
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A. Yes, since 45 is larger than 40.
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B. Yes, since the height of the dotplot above 45 is smaller than the height
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of thedotplot above 40.
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FOR INSTRUCTOR USE ONLY d d d
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