Goodness of Fit Before the Gondola was in operation, Heavenly tracked its skiers and boarders and found the following
With the new gondola in place the ski resort wants to determine if the distribution has changed. They tracked 2000 skiers and boarders and came up with the following
What can be concluded (use a = .05)?
Solution We first write determine the null and alternative hypotheses H_{0}: The new population of skiers and boarders follows the same distribution as the old distribution of skiers. H_{1}: The new population of skiers and boarders does not follow the same distribution as the old distribution of skiers. Next we compute the expected counts by multiplying the sample size 2000 by the expected percent.
Now add up the total of the last column to get 0.167 + 4.5 + 0 + 12.5 = 17.17 The number of degrees of freedom is df = n  1 = 4  1 = 3 where n is the number of rows in the table. We use the table for the Chi Square distribution. The critical value that corresponds to a level of significance of .05 with 3 degrees of freedom is 7.81. Since 17.17 > 7.81 we can reject the null hypothesis and accept the alternative hypothesis and conclude that the distribution of skiers and boarders has changed. An applet that does goodness of fit computations can be found here
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