91Ó°ÊÓ

The level of significance \(\alpha =0.01\)

Consider the below test hypothesis.

Null hypothesis:

\(H_{0}\): There is no association between BMD and depression.

Alternative hypothesis:

\(H_{a}\):There is association between BMD and depression.

By using any software perform the chi-square homogeneity test to find the test statistic.

Enter the given data,

Then we get, the chi-square static as \(10.095, p-value=0.006\)

Then, we have the

the rejection rule:

\(p-value \leq \alpha\), then null hypothesis rejected.

The level of significance \(\alpha =0.01\)

Here , clearly \(p-\)value is less than the level of significance.

\(p-value (0.006)<\alpha (0.01)\)

So, the null hypothesis is rejected at \(1%\) significant level.

Thus the results are statistically significant at \(1%\) significant level.

Hence,

The data provide is sufficient evidence to conclude that BMD and depression are statistically dependent for elderly Asian men.