Contents
For what purpose is the F test used?
The F-test is used by a researcher in order to carry out the test for the equality of the two population variances. If a researcher wants to test whether or not two independent samples have been drawn from a normal population with the same variability, then he generally employs the F-test.
How do I compare two means in SPSS?
To open the Compare Means procedure, click Analyze > Compare Means > Means. A Dependent List: The continuous numeric variables to be analyzed. You must enter at least one variable in this box before you can run the Compare Means procedure.
How to compare two populations from independent populations?
As with comparing two population proportions, when we compare two population means from independent populations, the interest is in the difference of the two means. In other words, if μ 1 is the population mean from population 1 and μ 2 is the population mean from population 2, then the difference is μ 1 − μ 2.
Which is the best test for comparing two population variances?
Minitab offers three (3) different methods to test equal variances. The F-test: This test assumes the two samples come from populations that are normally distributed. Bonett’s test: this assumes only that the two samples are quantitative. Levene’s test: similar to Bonett’s in that the only assumption is that the data is quantitative.
How to compare two populations by mean and standard deviation?
Each population has a mean and a standard deviation. We arbitrarily label one population as Population 1 and the other as Population 2, and subscript the parameters with the numbers 1 and 2 to tell them apart. We draw a random sample from Population 1 and label the sample statistics it yields with the subscript 1.
Where does the difference in population means lie?
We are 99% confident that the difference in the population means lies in the interval [0.15, 0.39], in the sense that in repeated sampling 99% of all intervals constructed from the sample data in this manner will contain μ1 − μ2.