Use this one-sided test to determine whether the population mean is less than the hypothesized mean. This one-sided test has greater power than a two-sided test, but it cannot determine whether the population mean is greater than the hypothesized mean.
For example, a quality analyst uses this one-sided test to be certain that the mean concentration of solids in water is less than 22.4 mg/L. This one-sided test has greater power to determine whether the mean is less than 22.4 mg/L, but it cannot determine whether the mean is greater than 22.4 mg/L.
Use this two-sided test to determine whether the population mean differs from the hypothesized mean. A two-sided test can detect differences that are less than or greater than the hypothesized value, but it has less power than a one-sided test.
For example, an engineer wants to know if the mean length of pencils is different from the target of 18.85 cm. Because any difference from the target is important, the engineer uses this two-sided test to determine whether the mean is greater than or less than the target.
Use this one-sided test to determine whether the population mean is greater than the hypothesized mean. This one-sided test has greater power than a two-sided test, but it cannot determine whether the population mean is less than the hypothesized mean.
For example, a hospital administrator uses this one-sided test to determine whether the mean rating on a patient satisfaction survey is greater than 90. This one-sided test has greater power to determine whether the mean rating is greater than 90, but it cannot determine whether the mean rating is less than 90.
For more information on selecting a one-sided or two-sided alternative hypothesis, go to About the null and alternative hypotheses.
Select to store the mean from each resample in the worksheet. Minitab stores the values in the column Means after the last column of data.
Minitab adjusts the data so that the center of the resamples is the same as the hypothesized mean. First, Minitab calculates the difference between the hypothesized mean and the mean of the original sample. Then Minitab adds or subtracts the difference to each value in the original sample. Resamples are taken from this adjusted data.
(Optional) In Base for random number generator, you can specify the starting point for the random selection of the bootstrapping sample by entering an integer that is greater than or equal to 1. When you use the same base number, you get the same sample.
For example, a professor generates 50 resamples of the original data for use in a classroom exercise. The professor and students each set the base to 1 to generate the same bootstrapping distribution and thus, the same analysis results.