You want to make a confidence interval for the population proportion of people between years old who have gotten a speeding ticket in the past years. A prior study found that of people between years old have received a speeding ticket in the last year. If you want your estimate to be accurate within of the true population proportion, what is the minimum sample size needed?
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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An economist is evaluating how frequently the U.S. inflation rate exceeds the Federal Reserve's long-term target of 2% per yr≈0.17% per month. The economist finds that in 34 of the 48 sampled months, the monthly inflation rate did exceed 0.17%.
Under stable conditions the inflation rate should not exceed the target more than of the time. Can the economist conclude that inflation has exceeded the target more than ?
A
No since is in (0.61,0.75).
B
Yes since is not in (0.58,0.84).
C
No since 0.2 is not in (0.58,0.84).
D
Yes since 0.2 is in (0.61,0.75).

1
Step 1: Define the null hypothesis (H0) and the alternative hypothesis (H1). The null hypothesis (H0) states that the proportion of months where inflation exceeds the target is 20% (p = 0.20). The alternative hypothesis (H1) states that the proportion of months where inflation exceeds the target is greater than 20% (p > 0.20).
Step 2: Calculate the sample proportion (p̂). The sample proportion is the number of months where inflation exceeded the target divided by the total number of months sampled. Use the formula: p̂ = x / n, where x is the number of successes (34 months) and n is the total sample size (48 months).
Step 3: Compute the standard error (SE) of the sample proportion. The standard error is calculated using the formula: SE = sqrt((p0 * (1 - p0)) / n), where p0 is the hypothesized proportion (0.20) and n is the sample size (48).
Step 4: Calculate the z-test statistic. The z-test statistic is computed using the formula: z = (p̂ - p0) / SE, where p̂ is the sample proportion, p0 is the hypothesized proportion, and SE is the standard error calculated in Step 3.
Step 5: Compare the z-test statistic to the critical value or p-value. For a one-tailed test at a significance level of 0.05, the critical z-value is approximately 1.645. If the z-test statistic is greater than 1.645, reject the null hypothesis (H0) and conclude that inflation has exceeded the target more than 20% of the time. Otherwise, fail to reject the null hypothesis.
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