Increasing the sample size increases the power of your test. If you provide the sample size, difference, and estimated standard deviation, 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 cooking oil data, the graph displays one power curve for each sample size. The power curves represent every combination of power and difference based on sample sizes of 24, 27, 32, and 40. The symbol on each power curve represents the test's power for detecting a difference of 1.5%.

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