This document provides an overview of common statistical hypothesis tests, including: 1. One-tail and two-tail t-tests of hypotheses for the mean to compare a sample mean to a hypothesized population mean or compare two independent sample means. 2. Z-tests of hypotheses for a proportion to test a claim about a population proportion or compare two independent proportions. 3. Pooled variance t-tests to compare two independent sample means when population variances are unknown but assumed equal. Worked examples are provided to demonstrate how to set up the null and alternative hypotheses, calculate test statistics, determine critical values, and make decisions to reject or fail to reject the null hypothesis.

1. Statistics for Management Fundamentals of Hypothesis Testing

4. Example: One Tail t-Test Does an average box of cereal contain more than 368 grams of cereal? A random sample of 36 boxes showed X = 372.5 , and  S= 15 . Test at the  0.01 level. 368 gm. H 0 :   368 H 1 :  368  is not given,

17. t X X S n n S n S n S n n P P                            1 2 1 2 2 1 2 2 1 1 2 2 2 2 1 2 2 2 3 27 2 53 0 1 510 21 25 2 03 1 1 1 1 21 1 1 30 25 1 1 16 21 1 25 1 1 510   . . . . . . . Calculating the Test Statistic: ( ( ( ( ( ( ( ( ( ( ( ) ) ) ) ) ) ) ) ) ) )