# Module 4 Exercise 2

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In dealing with non-pooled statistics in two different scenarios, or samples in this case. One is Standard Deviations and Assumed Equal. You can be somewhat certain that the populations have nearly equal standard deviations, and then you should use a pooled-t method. If you were really uncertain then you would use a non-pooled t-method. And with the SRS’s separate samples or normal populations, large samples are not satisfied; then the non-pooled-t methods should not be used.

As for two population means using paired samples. In each paired sample there will be a member of one population and then a member of the second group. For the simple random paired sample each one that is already selected.

Confidence intervals for one population proportion. The margin of error is quite simple; it explains how precise your estimates can be. The book states that; “the margin of error of an estimator represents the precision with which it estimates the parameter in question.” This section talks about proportions of sample (p) and population (p) determine the margin of error and then briefly mentions the sample sizes of estimating (p).

There are also hypotheses test for one population proportion. The one proportion z-test is also known as the one sample z-test for a population and the one variable proportion test. The proportion z-test can be performed by figuring out if the hypothesis is right, left, or two-tailed. Once you have figured out that you can move onto significance level, grabbing the value of the test you get a statistic. Then move on to the interpreting results from the hypothesis.

In the reference for two proportions, to derive a confidence-interval procedure for the difference between two population proportions, called the two-proportions z-interval procedure.

The purpose for this is to find a confidence interval for the difference between two population proportions, p1 and p2.

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