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1 Review and Practice Exam Questions for Exam 2 Learning Objectives: Chapter 17: Thinking about chance • Explain how random events behave in the short run and in the long run and how random and haphazard are not the same thing. • Perform basic probability calculations using die rolls and coin tosses. • Define probability, and apply the rules for probability. • Explain whether the law of averages is true. • Explain how personal probability differs from a scientific or experimental probability. Chapter 18: Probability models • Define a probability model. Create a probability model for a particular story’s events. • Apply the basic rules of probability to a story problem. • Calculate probabilities using a probability model, including summing up probabilities or subtracting probabilities from the total. • Define a sampling distribution. Chapter 20: The house edge: expected values • Define expected value, and calculate the expected value when given a probability model. • Define the law of large numbers, and explain how it is different from the mythical “law of averages.” • Explain how casinos and insurance companies stay in business and make money. Chapter 13: The Normal distribution • Identify data that is Normally distributed. • Discuss how the shape/position of the Normal curve changes when the standard deviation increases/decreases or when the mean increases/decreases. • Define the standardized value or Z-score. Calculate the Z-score, and use the Z-score to do comparisons. • Calculate probabilities and cut-off values using the 68%-95%-99.7% (Empirical) Rule. • Identify the mean, standard deviation, cut-off value, probability, and Z-score on a Normal curve. • Use the Normal table to get percentiles (probabilities) for forward problems and to get Z-scores in order to determine cut-offs for backward problems using both > and < in the inequalities. • Recognize whether a story is a forward or backward Normal distribution problem, and perform the appropriate calculations showing correct notation, the initial probability expression, and all necessary steps. 2 Chapter 21: What is a confidence interval? • Define statistical inference and explain when statistical inference is used. • Explain what the confidence interval means and whether the results refer to the population or the sample. • Calculate the margin of error and identify the margin of error in a confidence statement. Explain what type of error is covered in the margin of error. • Determine whether a story is better described with a proportion or a mean. • Use appropriate notation for proportions and means, both in the population and the sample. • Calculate a confidence interval for a proportion and for a mean. • Describe how increasing/decreasing the sample size or confidence level changes the margin of error (width of the confidence interval). • Apply cautions for using confidence inte ...
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Chapter 5
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Chapter 5: Probability
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Example: Boredom Tolerance
Test 400 6 1,600 5 4,400 4 6,000 3 3,600 2 2,600 1 1,400 0 Number of Subjects Score Boredom Tolerance Test Scores for 20,000 Subjects
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