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A contingency table is constructed that shows the number of passengers who survived/died according to whether they were male, female, boy or girl.

It is known that the tests of independence with a contingency table are always right-tailed.

In the test of independence of attributes, the chi-square test statistic is as follows:

\({\chi ^2} = \sum {\frac{{{{\left( {O - E} \right)}^2}}}{E}} \)

Suppose the discrepancy between the observed and expected frequencies is considerable. In that case, the test statistic value will shift to the right side of the curve, indicating the rejection of the null hypothesis (if it exceeds a certain value). Also, a large deviation means that the observed frequencies do not match the expected frequencies and the two attributes are not independent.

Furthermore, if the difference between the observed and the expected frequencies is less, the test statistic value will shift to the left side of the curve, implying that the given frequencies match the expected frequencies. As a result, the two attributes will be independent.

The claim to be tested is that the passenger鈥檚 survival is independent of whether the person is a man, woman, boy or a girl.

This implies that it is the independence of attributes test.

Therefore, the given hypothesis test is said to be a right-tailed test.