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19 of 22 participants (86.36%) from the high-power posing group took a gambling risk to double their money, while 12 of 20 (60%) from the low-power posing group took the gambling risk. Use a calculator tool from Module 10 to determine the p-value associated with the hypothesis test examining if there is a statistically significant difference between the proportion of people willing to take risks in the two groups. Round to 3 decimal places.

User DovaX
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Final answer:

To determine the p-value for the difference in the proportion of people taking risks between high-power and low-power posing groups, the 2-PropZTest function is used, which may lead to rejecting the null hypothesis if the p-value is low enough, such as 0.0417.

Step-by-step explanation:

To calculate the p-value for the hypothesis test that examines if there is a statistically significant difference between the proportions of people willing to take risks in the high-power and low-power posing groups, we can use a calculator function like 2-PropZTest. This statistical tool will analyze the proportion of participants from each group that decided to take a gambling risk and will return the p-value associated with the test.

The results of the tests show that 19 of 22 participants in the high-power posing group (86.36%) and 12 of 20 participants in the low-power posing group (60%) took the risk. Applying these figures to a 2-PropZTest calculator function would yield the p-value. In the context of this statistical question, if we receive a p-value of 0.0417, it implies that at a significance level of, for example, 5% (α = 0.05), there is sufficient evidence to reject the null hypothesis. This means there may be a statistically significant difference in the proportion of individuals willing to take risks between the two posing groups.

User Bikee
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