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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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TB Introduction To Statistical Investiga-
tionsb 2nd Edition Beth L.Chance
Chapter 1
Introduction to Statistical Investigations Test Bank
Note: TE = Text entry TE-N = Text entry - Numeric
Ma = Matching MS = Multiple select
MC = Multiple choice TF = True-False
E = Easy, M = Medium, H = Hard
CHAPTER 1 LEARNING OBJECTIVES
CLO1-1: Use the chance model to determine whether an observed statistic is unlikely to occur.
CLO1-2: Calculate and interpret a p-value, and state the strength of evidence it provides against
the null hypothesis.
CLO1-3: Calculate a standardized statistic for a single proportion and evaluate the strength of
evidence it provides against a null hypothesis.
CLO1-4: Describe how the distance of the observed statistic from the parameter value specified
by the null hypothesis, sample size, and one- vs. two-sided tests affect the strength of
evidence against the null hypothesis.
CLO1-5: Describe how to carry out a theory-based, one-proportion z-test.
Section 1.1: Introduction to Chance Models
LO1.1-1: Recognize the difference between parameters and statistics.
LO1.1-2: Describe how to use coin tossing to simulate outcomes from a chance model of the ran-
dom choice between two events.
LO1.1-3: Use the One Proportion applet to carry out the coin tossing simulation.
LO1.1-4: Identify whether or not study results are statistically significant and whether or not the
chance model is a plausible explanation for the data.
LO1.1-5: Implement the 3S strategy: find a statistic, simulate results from a chance model, and
comment on strength of evidence against observed study results happening by chance
alone.
LO1.1-6: Differentiate between saying the chance model is plausible and the chance model is the
correct explanation for the observed data.
FOR INSTRUCTOR USE ONLY
,1-2 Test Bank for Introduction to Statistical Investigations, 2nd Edition
Questions 1 through 4:
Do red uniform wearers tend to win more often than those wearing blue uniforms in
Taekwondo matches where competitors are randomly assigned to wear either a red or
blue uniform? In a sample of 80 Taekwondo matches, there were 45 matches where the
red uniform wearer won.
1. What is the parameter of interest for this study?
A. The long-run proportion of Taekwondo matches in which the red uniform wearer
wins
B. The proportion of matches in which the red uniform wearer wins in a sample of 80
Taekwondo matches
C. Whether the red uniform wearer wins a match
D. 0.50
Ans: A; LO: 1.1-1; Difficulty: Easy; Type: MC
2. What is the statistic for this study?
A. The long-run proportion of Taekwondo matches in which the red uniform wearer
wins
B. The proportion of matches in which the red uniform wearer wins in a sample of 80
Taekwondo matches
C. Whether the red uniform wearer wins a match
D. 0.50
Ans: B; LO: 1.1-1; Difficulty: Easy; Type: MC
3. Given below is the simulated distribution of the number of ―red wins‖ that could happen by
chance alone in a sample of 80 matches. Based on this simulation, is our observed result
statistically significant?
A. Yes, since 45 is larger than 40.
B. Yes, since the height of the dotplot above 45 is smaller than the height of the
dotplot above 40.
C. No, since 45 is a fairly typical outcome if the color of the winner‘s uniform was
determined by chance alone.
FOR INSTRUCTOR USE ONLY
, Introduction to Financial Statements 1-3
D. No, since we could have observed a value greater than 45 just by random chance.
Ans: C; LO: 1.1-4; Difficulty: Medium; Type: MC
4. What can we conclude from the results of this study? Select all that apply.
A. The results of this study are something that could easily have happened if the
color of the winner‘s uniform was determined by chance alone.
B. We do not have convincing evidence against the ―by-chance-alone‖ model.
C. The results of this study prove that the color of the winner‘s uniform was
determined by chance alone.
D. We do not have convincing evidence that red uniform wearers tend to win more
often than those wearing blue uniforms.
Ans: A, B, D; LO: 1.1-6; Difficulty: Hard; Type: MS
Questions 5 through 8:
Suppose you are testing to see if your dog, Hope, understands pointing towards an object. You
place two objects about 2.5 meters away, then you point towards one of the objects. In 20 trials,
Hope goes to the correct object 13 times (or 65%).
5. Fill in the blanks with the correct One Proportion applet inputs to carry out an appropriate
simulation of this process, if Hope does not understand pointing towards an object and is
just guessing.
Probability of success:
Sample size:
Number of samples:
Ans: 0.5 (Tol: 0), 20 (Tol: 0), Any integer as larger or larger than 1000; LO: 1.1-3;
Difficulty: Easy; Type: TE-N
6. Match the parts of the real study corresponding to the physical (coin-flipping) simulation:
Coin flip = A. 0.5, probability of Hope going to the
correct object
Heads =
B. Hope going to the correct object
Tails =
C. Hope going to the incorrect object
Chance of heads =
D. One set of 20 attempts by Hope
One repetition =
E. Hope going to an object
Ans: E, B, C, A, D; LO: 1.1-2; Difficulty: Medium; Type: Ma
FOR INSTRUCTOR USE ONLY
, 1-4 Test Bank for Introduction to Statistical Investigations, 2nd Edition
7. Given below is the resulting simulation distribution from the One Proportion applet. Based
on this simulation, do we have convincing evidence against the observed study results
happening by chance alone?
A. No, since 0.65 is a fairly typical outcome if Hope was just guessing.
B. No, since we could have observed a value greater than 0.65 just by random
chance.
C. Yes, since 0.65 is larger than 0.5.
D. Yes, since the height of the dotplot above 0.65 is smaller than the height of the
dotplot above 0.5.
Ans: A; LO: 1.1-5; Difficulty: Medium; Type: MC
8. Which of the following is NOT a step in the 3S Strategy for measuring strength of
evidence?
A. Strength of evidence
B. Statistic
C. Sample
D. Simulate
Ans: C; LO: 1.1-5; Difficulty: Easy; Type: MC
Questions 9 through 12:
True or False?
9. A parameter is a number summarizing the results in the sample.
Ans: False; LO: 1.1-1; Difficulty: Easy; Type: TF
10. A result that is unlikely to occur just by chance alone is called statistically significant.
Ans: True; LO: 1.1-4; Difficulty: Easy; Type: TF
11. If an observed statistic is statistically significant, then we have strong evidence that the
chance-alone explanation is correct.
Ans: False; LO: 1.1-5; Difficulty: Medium; Type: TF
12. If an observed statistic is NOT statistically significant, then the chance model is plausible.
FOR INSTRUCTOR USE ONLY
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