Posted by **War Eagle** on Sunday, December 1, 2013 at 8:14pm.

1. The Chi-square distribution, used in the Chi-square test of independence, varies in shape by degrees of freedom. What does the Chi-square distribution look like for 4 degrees of freedom.

A) Unimodal and symmetric.

B) Bimodal and symmetric.

C) Unimodal and skewed to the left.

D) Unimodal and skewed to the right.

2.The Chi-square distribution, used in the Chi-square test of independence, varies in shape by degrees of freedom. What does it mean when the Chi-square value is small and the p-value is large?

A) As the Chi-square value gets small, the probability value gets large. In this case you fail to reject Ho and believe the events are independent.

B) As the Chi-square value gets small, the probability value gets large. In this case you fail to reject Ho and believe the events are not independent.

C) As the Chi-square value gets small, the probability value gets large. In this case you reject Ho and believe the events are not independent.

D) As the Chi-square value gets small, the probability value gets large. In this case you reject Ho and believe the events are independent.

3. The χ2-test for independence is a useful tool for establishing a causal relationship between two factors.

A) True

B) False

1. B

2. D

3. A

Are my answers correct?

- Statistics -
**MathGuru**, Monday, December 2, 2013 at 5:28pm
1. D

Chi Square distributions are positively skewed (skewed to the right). As the degrees of freedom increases, the Chi Square distribution will approach a normal symmetrical distribution. Smaller degrees of freedom will skew more to the right.

2. A

Ho: The variables are independent.

Ha: The variables are not independent.

(Large p-values result in failing to reject Ho.)

3. B

The alternative hypothesis (Ha) suggests that the variables are related, but the relationship is not necessarily a causal one.

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