How to do a F test of two variances?

How to do a F test of two variances?

A supermarket might be interested in the variability of check-out times for two checkers. In order to perform a F test of two variances, it is important that the following are true: The populations from which the two samples are drawn are normally distributed. The two populations are independent of each other.

When to compare two variances rather than two averages?

It is often desirable to compare two variances rather than two averages. For instance, college administrators would like two college professors grading exams to have the same variation in their grading. In order for a lid to fit a container, the variation in the lid and the container should be the same.

How to calculate the variance of a sample?

What you’re thinking of is when we estimate the variance for a population [sigma^2 = sum of the squared deviations from the mean divided by N, the population size] or when estimating the variance for a sample [s^2 = sum of the squared deviations from the mean divided by n-1, where n = the sample size]. Comment on JMGClark’s post “Good question!

Which is the best tool to test for unequal variances?

We can also use Excel’s t-Test: Two-Sample Assuming Unequal Variances data analysis tool to get the same result (see Figure 2). Observation: Generally, even if one variance is up to 3 or 4 times the other, the equal variance assumption will give good results, especially if the sample sizes are equal or almost equal.

Is the variance in grades smaller for the first instructor?

Conclusion: With a 10% level of significance, from the data, there is sufficient evidence to conclude that the variance in grades for the first instructor is smaller. Press STAT and arrow over to TESTS.

How is the F distribution used in statistics?

Another of the uses of the F distribution is testing two variances. It is often desirable to compare two variances rather than two averages. For instance, college administrators would like two college professors grading exams to have the same variation in their grading.