Contents
How to test the ratio of two means?
State the statistical hypotheses in terms of the ratio of the means. 2. Transform this into hypotheses about a difference by taking logarithms. 3. Analyze the logged data—that is, do the analysis in terms of the difference. 4. Draw the conclusion in terms of the ratio. The details of step 2 for the two-sided null hypothesis are as follows:
The mean of the test sample is an estimate of the mean of the test population. The mean of the reference sample is an estimate of the mean of the reference population. Therefore, the ratio of the sample means provides an estimate of the ratio of the mean of the test population to the mean of the reference population.
How are means and proportions used in estimation?
In estimation we focused explicitly on techniques for one and two samples and discussed estimation for a specific parameter (e.g., the mean or proportion of a population), for differences (e.g., difference in means, the risk difference) and ratios (e.g., the relative risk and odds ratio).
How is the mean of a sample calculated in MINITAB?
If you selected a hypothesis about the ratio of the means, Minitab calculates the ratio of the mean of the test sample to the mean of the reference sample. The mean of the test sample is an estimate of the mean of the test population. The mean of the reference sample is an estimate of the mean of the reference population.
Where to find the difference in the 2 sample equivalence test?
Find definitions and interpretation guidance for every measure that is provided in the Difference (or Ratio) table of the 2-sample equivalence test. If you selected a hypothesis about the difference between means, Minitab displays the difference between the test mean and the reference mean from your samples.
How do you test two independent sample sizes?
The relevant sample data are the sample sizes in each comparison group (n 1 and n 2) and the sample proportions ( ) which are computed by taking the ratios of the numbers of successes to the sample sizes in each group, i.e., There are several approaches that can be used to test hypotheses concerning two independent proportions.