Increasing the sample size increases the power of your test. If you provide the sample size and ratio, Minitab calculates the power of the test. You can vary the sample size and hold the other assumptions constant to produce multiple power curves. This highlights the effect of different sample sizes on power.

For the lumber data, the graph displays one power curve for each sample size. The power curves represent every combination of power and ratio the test can detect based on a sample of size 53 and 68. The symbol on each power curve represents the test's power for detecting a ratio of 0.75.

The curves representing larger sample sizes yield higher power for any given difference when the other assumptions are held constant.