Increasing the sample size increases the power of your test. You want enough observations in your samples to achieve adequate power, but not so many that you waste time and money on unnecessary sampling.

If you indicate the power that you want the test to have and the ratio you want it to be able to detect, Minitab will calculate how large your samples must be. (Because sample sizes are given in integer values, the actual power may be slightly greater than your target value.)

For the lumber data, the manager wants to analyze the variability in length of lumber. He is interested in detecting a ratio of 0.75 between the alternative and hypothesized standard deviations. He wants to how many samples he needs to obtain a power value of 0.8 or 0.9.

The results indicate that the lumber company needs to collect 53 samples to obtain a power of 0.8 and 68 samples to obtain a power of 0.9.