A traffic safety consultant wants to compare the number of cars per hour that travel on two different streets. Before collecting the data for a 2-sample Poisson rate test, the consultant uses a power and sample size calculation. The consultant wants to determine how large of a sample size the test needs to obtain a power of 0.9 and detect a comparison rate of 32 or 38 (a difference of 3 from the baseline rate of 35).

- Choose .
- In Comparison rates (R1), enter
`32 38`. - In Power values, enter
`0.9`. - In Baseline rate (R2), enter
`35`. - Click OK.

To detect a comparison rate of 32 with a power value of 0.9, the consultant needs a sample size of 79. To detect a comparison rate of 38 with a power value of 0.9, the consultant needs a sample size of 86. The analyst decides to collect a sample size of 86 to give the test a power value of at least 0.9 for both comparison rates. Because the target power value of 0.9 results in a sample size that is not an integer, Minitab also displays the power (Actual Power) for the rounded sample size.

Test for 2-Sample Poisson Rate

Testing comparison rate = baseline rate (versus ≠)

Calculating power for baseline rate = 35

α = 0.05

“Lengths” of observation for sample 1, sample 2 = 1, 1

Comparison Rate | Sample Size | Target Power | Actual Power |
---|---|---|---|

32 | 79 | 0.9 | 0.902793 |

38 | 86 | 0.9 | 0.902550 |