QUESTION 1 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. QUESTION 2 While it may even be questionable that the research team reported a significant result at the 0.05 level based upon our findings in question 1, let's observe the major impact a slight change makes in our calculation. Recalculate the p-value from part 1, but let's pretend that 18 of the 22 participants in the high-power group took the gambling risk. This new p-value speaks to the volatility of results when low sample sizes are used. Round this p-value to 3 decimal places.

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QUESTION 1
2
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.
2
QUESTION 2
While it may even be questionable that the research team reported a significant result at the 0.05 level based upon our findings in question 1, let's observe the
major impact a slight change makes in our calculation. Recalculate the p-value from part 1, but let's pretend that 18 of the 22 participants in the high-power group
took the gambling risk. This new p-value speaks to the volatility of results when low sample sizes are used. Round this p-value to 3 decimal places.
Many researchers tried to replicate the power posing research without success. One researcher used a sample size of n=200 (100 in each group). Let's assume 86
of the 100 people in the high-power group in this ngw research took the gambling risk, and 79 of 100 people in the low-power group took the gambling risk. Perform
a hypothesis test to again detect a difference between the proportions willing to gamble from the two power posing groups, and state the resulting p-value. Round
to 3 decimal places.
QUESTION 3
.193
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Transcribed Image Text:A Sta t-test A blackboard.wccnet.edu/webapps/assessment/take/launch.jsp?course_assessment_id=_655580_1&course_id=_96297_1&content_id%3_7095083_1&step=null Re/Ap Bb 84752 TED Amy C S Tak X Apps WCC Gateway All apps | Microsof... A Winter 2020 MTH... V5 Announcements -.. 6 Launch Meeting -.. Your answers are saved automatically. * Question Completion Status: QUESTION 1 2 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. 2 QUESTION 2 While it may even be questionable that the research team reported a significant result at the 0.05 level based upon our findings in question 1, let's observe the major impact a slight change makes in our calculation. Recalculate the p-value from part 1, but let's pretend that 18 of the 22 participants in the high-power group took the gambling risk. This new p-value speaks to the volatility of results when low sample sizes are used. Round this p-value to 3 decimal places. Many researchers tried to replicate the power posing research without success. One researcher used a sample size of n=200 (100 in each group). Let's assume 86 of the 100 people in the high-power group in this ngw research took the gambling risk, and 79 of 100 people in the low-power group took the gambling risk. Perform a hypothesis test to again detect a difference between the proportions willing to gamble from the two power posing groups, and state the resulting p-value. Round to 3 decimal places. QUESTION 3 .193 Close Window Save All Answers Click Save and Submit to save and submit. Click Save All Answers to save all answers.
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t-test
A blackboard.wccnet.edu/webapps/assessment/take/launch.jsp?course_assessment_id=_655580_1&course_id=_96297_1&content_id=_7095083_1&step=null
| Apps
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A Winter 2020 MTH...
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QUESTION 3
Many researchers tried to replicate the power posing research without success. One researcher ed a sample size of n=200 (100 in each group). Let's assume 86
of the 100 people in the high-power group in this new research took the gambling risk, and 79 of 00 people in the low-power group took the gambling risk. Perform
a hypothesis test to again detect a difference between the proportions willing to gamble from the two power p ing groups, and state the resulting p-value. Round
to 3 decimal places.
.193
QUESTION 4
If Amy Cuddy and her research team originally established a sample size of n=200 (100 in each group) and then discovered that 86% of the high-power group (86 of
100) took a gambling risk while 60% of the low-power group (60 of 100) took the risk, then the p-value would have been much lower than that originally found in
question 1. This p-value would have been less sensitive and would have provided stronger evidence for the researcher's hypothesis. State the p-value, rounding to
5 decimal places.
QUESTION 5
O a. The manipulation of statistical analysis, perhaps unconsciously, to arrive at statistically significant results (p-values less than 0.05)
O b. A terrible cough that develops when calculating p-values
P-hacking is a definite concern in the research world. Look up this term and match it with the correct definition below.
OC. Hacking into another person's PC
O d. Unauthorized use of someone else's data
Save All Answers
QUESTION 6
Transcribed Image Text:494.T Death A The E E Untitle 2 Unbe Untitle V6 Lectu McGr ALEKS Re/Ap Bb 84752 TED Amy C Tal x t-test A blackboard.wccnet.edu/webapps/assessment/take/launch.jsp?course_assessment_id=_655580_1&course_id=_96297_1&content_id=_7095083_1&step=null | Apps WCC Gateway All apps | Microsof.. A Winter 2020 MTH... 36 Announcements -. O Launch Meeting -. * Question Completion Status: QUESTION 3 Many researchers tried to replicate the power posing research without success. One researcher ed a sample size of n=200 (100 in each group). Let's assume 86 of the 100 people in the high-power group in this new research took the gambling risk, and 79 of 00 people in the low-power group took the gambling risk. Perform a hypothesis test to again detect a difference between the proportions willing to gamble from the two power p ing groups, and state the resulting p-value. Round to 3 decimal places. .193 QUESTION 4 If Amy Cuddy and her research team originally established a sample size of n=200 (100 in each group) and then discovered that 86% of the high-power group (86 of 100) took a gambling risk while 60% of the low-power group (60 of 100) took the risk, then the p-value would have been much lower than that originally found in question 1. This p-value would have been less sensitive and would have provided stronger evidence for the researcher's hypothesis. State the p-value, rounding to 5 decimal places. QUESTION 5 O a. The manipulation of statistical analysis, perhaps unconsciously, to arrive at statistically significant results (p-values less than 0.05) O b. A terrible cough that develops when calculating p-values P-hacking is a definite concern in the research world. Look up this term and match it with the correct definition below. OC. Hacking into another person's PC O d. Unauthorized use of someone else's data Save All Answers QUESTION 6
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