4.2: Confidence Intervals
4.2.1: Confidence Intervals for Mean
This section explains the need for confidence intervals and why a confidence interval is not the probability the interval contains the parameter. Then, it discusses how to compute a confidence interval on the mean when sigma is unknown and needs to be estimated. It also explains when to use t-distribution or a normal distribution. Next, it covers the difference between the shape of the t distribution and the normal distribution and how this difference is affected by degrees of freedom. Finally, it explains the procedure to compute a confidence interval on the difference between means.
This demonstration provided here is a supplement to the previous section.
Read the instructions and watch the video to see how the degrees of freedom affect the difference between t and normal distributions.
This demonstration is a supplement to the previous materials.
4.2.2: Confidence Intervals for Correlation and Proportion
- First, this section shows how to compute a confidence interval for Pearson's correlation. The solution uses Fisher's z transformation. Then, it explains the procedure to compute confidence intervals for population proportions where the sampling distribution needs a normal approximation.
Watch these videos, which discuss confidence intervals.