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Ch. 7 - Estimating Parameters and Determining Sample Sizes
Triola - Elementary Statistics 14th Edition
Triola14th EditionElementary StatisticsISBN: 9780137366446당신이 사용하는 게 아니라요?교과서 변경
7장, 문제 7.1.19b

Critical Thinking. In Exercises 17–28, use the data and confidence level to construct a confidence interval estimate of p, then address the given question.


Tennis Challenges In a recent U. S. Open tennis tournament, women playing singles matches used challenges on 137 calls made by the line judges. Among those challenges, 33 were found to be successful with the call overturned.


b. Compare the result from part (a) to this 99% confidence interval for the percentage of successful challenges made by the men playing singles matches: . Does it appear that either gender is more successful than the other?

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Step 1: Identify the given data for the problem. The total number of challenges made by women is 137, and the number of successful challenges is 33. The confidence level is 99%.
Step 2: Calculate the sample proportion (p̂) of successful challenges for women. Use the formula: p̂ = x / n, where x is the number of successful challenges (33) and n is the total number of challenges (137).
Step 3: Determine the standard error (SE) for the sample proportion. Use the formula: SE = sqrt((p̂ * (1 - p̂)) / n), where p̂ is the sample proportion and n is the sample size.
Step 4: Find the critical value (z*) for a 99% confidence level. This value corresponds to the z-score that leaves 0.5% in each tail of the standard normal distribution. Commonly, z* for 99% confidence is approximately 2.576.
Step 5: Construct the confidence interval for the population proportion (p) using the formula: CI = p̂ ± z* * SE. Compare this confidence interval to the given 99% confidence interval for men’s successful challenges to determine if there is a significant difference between genders.

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주요 개념

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Confidence Interval

A confidence interval is a range of values, derived from sample statistics, that is likely to contain the true population parameter with a specified level of confidence. For example, a 99% confidence interval suggests that if we were to take many samples and construct intervals in the same way, approximately 99% of those intervals would contain the true proportion of successful challenges.
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06:33
Introduction to Confidence Intervals

Proportion

Proportion refers to the fraction of the total that possesses a certain characteristic. In this context, it is the ratio of successful challenges to the total number of challenges made. Understanding proportions is essential for comparing success rates between different groups, such as male and female players in the tennis tournament.
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가이드 코스
09:27
Difference in Proportions: Hypothesis Tests

Hypothesis Testing

Hypothesis testing is a statistical method used to make inferences about population parameters based on sample data. In this scenario, it involves comparing the proportions of successful challenges between genders to determine if there is a statistically significant difference in their success rates. This process typically includes formulating null and alternative hypotheses and calculating p-values.
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가이드 코스
06:21
Step 1: Write Hypotheses
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b. Are the requirements for constructing a 95% confidence interval estimate of the population standard deviation satisfied? If so, construct that confidence interval.


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b. Assume that sigma=11.3 bpm, based on the value of s=11.3 bpm for the sample of 153 male pulse rates.


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b. Use the information from a previous Harris survey in which 26% of respondents said that they believed in astrology.

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b. Assume that a previous study showed that 10% of adults can touch their nose with their tongue (based on data from Onedio).


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Critical Thinking. In Exercises 17–28, use the data and confidence level to construct a confidence interval estimate of p, then address the given question.


Job Interviews In a Harris poll of 514 human resource professionals, 45.9% said that body piercings and tattoos were big personal grooming red flags.


c. Repeat part (b) using a confidence level of 80%.


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Women Who Give Birth An epidemiologist plans to conduct a survey to estimate the percentage of women who give birth. How many women must be surveyed in order to be 99% confident that the estimated percentage is in error by no more than two percentage points?



c. What is wrong with surveying randomly selected adult women?

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