A factory manager wants to estimate the proportion of defective items produced. In a batch of 20 items, the factory has produced 6 with defects. Find the margin of error for a 98% confidence interval for the true proportion of defective items.
Table of contents
- 1. Introduction to Statistics53m
- 2. Describing Data with Tables and Graphs2h 1m
- 3. Describing Data Numerically1h 48m
- 4. Probability2h 26m
- 5. Binomial Distribution & Discrete Random Variables2h 55m
- 6. Normal Distribution & Continuous Random Variables1h 48m
- 7. Sampling Distributions & Confidence Intervals: Mean2h 8m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 20m
- 9. Hypothesis Testing for One Sample2h 23m
- 10. Hypothesis Testing for Two Samples3h 25m
- 11. Correlation1h 6m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 30m
- 14. ANOVA1h 4m
8. Sampling Distributions & Confidence Intervals: Proportion
Confidence Intervals for Population Proportion
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Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
Your company has asked you to estimate the proportion of people who prefer the color red over other primary colors for manufacturing purposes. If they want the estimate to be within .01 of the true proportion with 95% confidence, how many people should you survey?
A
1825
B
6766
C
9604
D
97

1
Identify the formula for sample size estimation in proportion problems: \( n = \frac{{Z^2 \, p \, (1-p)}}{{E^2}} \), where \( n \) is the sample size, \( Z \) is the Z-score corresponding to the desired confidence level, \( p \) is the estimated proportion, and \( E \) is the margin of error.
Determine the Z-score for a 95% confidence level. The Z-score for 95% confidence is typically 1.96.
Assume an estimated proportion \( p \). If no prior estimate is available, use \( p = 0.5 \) as it maximizes the sample size.
Set the margin of error \( E \) to 0.01, as specified in the problem.
Substitute the values into the formula: \( n = \frac{{(1.96)^2 \, 0.5 \, (1-0.5)}}{{(0.01)^2}} \) and solve for \( n \) to find the required sample size.
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