Internet Exercises - Speech or Presentation Example

By extreme we mean: far from what we would expect to observe if the null hypothesis is true. In other words, a small P-value indicates that observation of the test statistic would be unlikely if the null hypothesis is true. The lower the P-value, the more evidence there is in favor of rejecting the null hypothesis. The z-test for a mean is a statistical test for a population mean. The z-test can be used when the population is normal and σ is known, or for any population when the sample size n is at least 30.

The test statistic is the sample mean and the standardized test statistic is z. A chi-square test can be used to test if the variance (square of standard deviation) of a population is equal to a specified value. This test can be either a two-sided test or a one-sided test. The two-sided version tests against the alternative that the true variance is either less than or greater than the specified value. The one-sided version only tests in one direction. The choice of a two-sided or one-sided test is determined by the problem.

For example, if we are testing a new process, we may only be concerned if its variability is greater than the variability of the current process. Sample Problem: A hospital administrator believes that the standard deviation of the number of people using outpatient surgery per day is greater than 8. A random sample 15 days is selected. The data are shown. At α = 0.10, is there enough evidence to support the administrator’s claim? Assume the variable is normally distributed. Sample Problem: A researcher wanted to see if women varied more than men in weight.

  Nine women and sixteen men were weighed.  The variance for the women was 525 and the variance for the men was 142.  What can be concluded at the 0.05 level of significance? Since we are testing to see if the variance for the women