91Ó°ÊÓ

The observations for arrival time are known, along with the SPSS output.

Let there be three hypothesis tests to compare the mean arrival delay time of three flights.

\(\begin{aligned}{l}{H_0}:{\mu _1} = {\mu _2}\\{H_0}:{\mu _2} = {\mu _3}\\{H_0}:{\mu _1} = {\mu _3}\end{aligned}\)

Assume that each of the hypothesis tests is tested on a 0.05 significance level or 0.95 level of confidence.

To test three different hypotheses, the level of confidence transforms to\({0.95^3} = 0.857\).

The associated level of significance for the overall test of the three hypotheses is \(1 - 0.857 = 0.143\).

When the significance level is as high as 0.143,the type 1 error increases as a result of testing three pairs of hypotheses.

Consequently, the chances ofobtaining the result for the test accurately lower.

On the other hand, ANOVA is used to conduct the test at a 0.05 level of significance, which results in better accuracy.

Thus, conducting three different hypothesis tests is not preferred.