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

Consider the below test hypothesis.

Null hypothesis:

\(H_{0}\): There is no association between worry about gang attack and actually being a victim of a gang attack

Alternative hypothesis:

\(H_{a}\): There is association between worry about gang attack and actually being a victim of a gang attack.

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 \(=23.455, p-value=0.00\)

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.

\(p-value (0.00)<\alpha (0.01)\)

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 worry about gang attack and actually being a victim of a gang attack.