Objectives
Upon successful completion of this lesson, you should be able to:
- Identify situations in which the z or t distribution may be used to approximate a sampling distribution
- Construct a confidence interval to estimate the difference in two population proportions and two population means using Minitab given summary or raw data
- Conduct a hypothesis test for two proportions and two means using Minitab given summary or raw data
| Confidence Interval | Test Statistic | |
|---|---|---|
| Two Independent Proportions At least 10 successes and 10 failures in both samples. |
\((\widehat{p}_1-\widehat{p}_2) \pm z^\ast {\sqrt{\dfrac{\widehat{p}_1 (1-\widehat{p}_1)}{n_1}+\dfrac{\widehat{p}_2 (1-\widehat{p}_2)}{n_2}}}\) | \(z=\dfrac{\widehat{p}_1-\widehat{p}_2}{\sqrt{\widehat{p}(1-\widehat{p})\left ( \dfrac{1}{n_1}+\dfrac{1}{n_2} \right )}}\) |
| Two Independent Means Both sample size are at least 30 OR populations are normally distributed. |
\((\bar{x}_1-\bar{x}_2) \pm t^\ast{ \sqrt{\dfrac{s_1^2}{n_1}+\dfrac{s_2^2}{n_2}}}\) \(Estimated \;df = smallest\; n - 1\) |
\(t=\dfrac{\bar{x}_1-\bar{x}_2}{ \sqrt{\dfrac{s_1^2}{n_1}+\frac{s_2^2}{n_2}}}\) \(Estimated \;df = smallest\; n - 1\) |