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Ch. 7 - Estimating Parameters and Determining Sample Sizes
Triola - Elementary Statistics 14th Edition
Triola14th EditionElementary StatisticsISBN: 9780137366446Non è quello che usi tu?Cambia libro di testo
Capitolo 7, Problema 7.1.14

Constructing and Interpreting Confidence Intervals. In Exercises 13–16, use the given sample data and confidence level. In each case, (a) find the best point estimate of the population proportion p; (b) identify the value of the margin of error E; (c) construct the confidence interval; (d) write a statement that correctly interprets the confidence interval.


Eliquis The drug Eliquis (apixaban) is used to help prevent blood clots in certain patients. In clinical trials, among 5924 patients treated with Eliquis, 153 developed the adverse reaction of nausea (based on data from Bristol-Myers Squibb Co.). Construct a 99% confidence interval for the proportion of adverse reactions.

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Step 1: Identify the sample proportion (p̂). The sample proportion is calculated as the number of successes (nausea cases) divided by the total sample size. Use the formula: p̂ = x / n, where x = 153 (number of nausea cases) and n = 5924 (total patients).
Step 2: Determine the critical value (z*) for a 99% confidence level. The critical value corresponds to the z-score that leaves 0.5% in each tail of the standard normal distribution. You can find this value using a z-table or statistical software.
Step 3: Calculate the margin of error (E). Use the formula: E = z* × √(p̂(1 - p̂) / n). Substitute the values of p̂, z*, and n into the formula to compute E.
Step 4: Construct the confidence interval. The confidence interval is given by: p̂ - E < p < p̂ + E. Substitute the values of p̂ and E to find the lower and upper bounds of the interval.
Step 5: Interpret the confidence interval. Write a statement explaining that you are 99% confident the true population proportion of patients experiencing nausea as an adverse reaction lies within the calculated interval.

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Point Estimate

A point estimate is a single value that serves as a best guess or approximation of a population parameter, such as the population proportion p. In the context of the given question, the point estimate for the proportion of patients experiencing nausea would be calculated by dividing the number of patients who experienced the reaction by the total number of patients in the sample.
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Introduction to Confidence Intervals

Margin of Error

The margin of error (E) quantifies the uncertainty associated with a point estimate. It reflects the range within which the true population parameter is expected to lie, based on the sample data. The margin of error is influenced by the confidence level and the sample size, and it is crucial for constructing confidence intervals.
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Finding the Minimum Sample Size Needed for a Confidence Interval

Confidence Interval

A confidence interval is a range of values, derived from the sample data, that is likely to contain the true population parameter with a specified level of confidence. For example, a 99% confidence interval means that if the same sampling method were repeated multiple times, approximately 99% of the calculated intervals would contain the true population proportion. This interval is constructed using the point estimate and the margin of error.
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Introduction to Confidence Intervals
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Domanda del libro di testo

In Exercises 5–8, (a) identify the critical value ta/2 used for finding the margin of error, (b) find the margin of error, (c) find the confidence interval estimate of u, and (d) write a brief statement that interprets the confidence interval.


Pepsi Weights Here are summary statistics for the weights of Pepsi in randomly selected cans: n=36, x=0.82410 lb, s=0.00570 lb (based on Data Set 37 “Cola Weights and Volumes” in Appendix B). Use a confidence level of 99%.

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Red Blood Cell Count Here is a 95% confidence interval estimate of obtained by using the red blood cell counts of adult females listed in Data Set 1 “Body Data” in Appendix B:

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Identify the corresponding confidence interval estimate of and include the appropriate units.

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FINDING SAMPLE SIZE Instead of using Table 7-2 for determining the sample size required to estimate a population standard deviation σ, the following formula can also be used


n=12(zα/2d)2n=\(\frac{1}{2}\)\(\left\)(\(\frac{z_{\alpha/2}\)}{d}\(\right\))^2


where zα/2z_{_{}\(\alpha\)/2} corresponds to the confidence level and d is the decimal form of the percentage error. For example, to be 95% confident that s is within 15% of the value of σ, use zα/2=1.96 and d=0.15 to get a sample size of n=86. Find the sample size required to estimate the standard deviation of IQ scores of data scientists, assuming that we want 98% confidence that s is within 5% of σ.

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Job Interviews In a Harris poll of 514 human resource professionals, 463 said that the appearance of a job applicant is most important for a good first impression. Use 1000 bootstrap samples to construct a 99% confidence interval estimate of the proportion of all human resource professionals believing that the appearance of a job applicant is most important for a good first impression. How does the result compare to the confidence interval found in Exercise 24 part (b) in Section 7-1?

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Minting Quarters Listed below are weights (grams) of quarters minted after 1964 (based on Data Set 40 “Coin Weights” in Appendix B). Construct a 95% confidence interval estimate of the mean weight of all quarters minted after 1964. Specifications require that the quarters have a weight of 5.670 g. What does the confidence interval suggest about that specification?


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Atkins Weight Loss Program In a test of weight loss programs, 40 adults used the Atkins weight loss program. After 12 months, their mean weight loss was found to be 2.1 lb, with a standard deviation of 4.8 lb. Construct a 90% confidence interval estimate of the mean weight loss for all such subjects. Does the Atkins program appear to be effective? Does it appear to be practical?

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