A social scientist is interested in determining if there is a significant difference in the proportion of Republicans between two areas of town. He takes independent random samples of 20 families in each area of town and a significance test was conducted. The p-value was 0.106.

What should be our conclusions?

A. The evidence is very strong - there is a difference in proportion of Republicans between the two areas of town.

B. The evidence is very strong - there is NO difference in the proportion of Republicans between the two areas of town.

C. We do not have enough statistical evidence to say that there is a significant difference in the proportion of Republicans between two areas of town.

Question

Sunday

Mathematics

27 February, 05:09

A social scientist is interested in determining if there is a significant difference in the proportion of Republicans between two areas of town. He takes independent random samples of 20 families in each area of town and a significance test was conducted. The p-value was 0.106.

What should be our conclusions?

A. The evidence is very strong - there is a difference in proportion of Republicans between the two areas of town.

B. The evidence is very strong - there is NO difference in the proportion of Republicans between the two areas of town.

C. We do not have enough statistical evidence to say that there is a significant difference in the proportion of Republicans between two areas of town.

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Answers (1)

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Carolina Brown · Answer 1

B. The evidence is very strong - there is NO difference in the proportion of Republicans between the two areas of town.

Step-by-step explanation: Generally, a p-value of less than 0.05 is described as a strong evidence in favour of the null hypothesis. A p-value also known as the probability value is also known to provide the smallest level of evidence at which the null hypothesis would be rejected.

In the question, The p-value is 0.105 which is bigger in value than 0.05 which means there is no significant difference between the evidence and the null hypothesis.