Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample1h 1m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
10. Hypothesis Testing for Two Samples
Two Proportions
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Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
The data below is taken from two random, independent samples. Calculate the margin of error for a 99% confidence interval for the difference in population proportions.
,
,
A
0.061
B
0.062
C
0.158
D
0.060

1
Step 1: Understand the problem. We are tasked with calculating the margin of error for a 99% confidence interval for the difference in population proportions. The given data includes the sample successes (xâ‚ = 87, xâ‚‚ = 68) and sample sizes (nâ‚ = 120, nâ‚‚ = 115).
Step 2: Calculate the sample proportions for each group. The sample proportion for group 1 is p̂₠= xâ‚ / nâ‚, and for group 2, it is p̂₂ = xâ‚‚ / nâ‚‚. Use these formulas to compute the sample proportions.
Step 3: Compute the standard error (SE) for the difference in proportions. The formula for SE is: SE = sqrt((pÌ‚â‚(1 - pÌ‚â‚) / nâ‚) + (p̂₂(1 - p̂₂) / nâ‚‚)). Substitute the values of pÌ‚â‚, p̂₂, nâ‚, and nâ‚‚ into this formula.
Step 4: Determine the critical value (z*) for a 99% confidence level. For a 99% confidence interval, the z* value corresponds to the 99% level of confidence, which is approximately 2.576. This value is derived from the standard normal distribution.
Step 5: Calculate the margin of error (ME). The formula for ME is: ME = z* × SE. Multiply the critical value (z*) by the standard error (SE) to find the margin of error.
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