I need help answering #4. Finding p-value 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 grouptook 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.QUESTION 3Many 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 86of the 100 people in the high-power group in this new research took the gambling risk, and 79 of 100 people in the low-power group took the gambling risk. Performa 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. Roundto 3 decimal places..193QUESTION 4If 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 of100) took a gambling risk while 60% of the low-power group (60 of 100) took the risk, therythe p-value would have been much lower than that originally found inwould have been less sensitive and would have provided stronger evidence for the researcher's hypothesis. State the p-value, rounding to1. This p-v5 decimal places.Click Save and Submit to save and submit. Click Save All Answers to save all answers.Save All AnswersMacBook AirDIIDD888F6F7FBF9F2F3F4F5@$% BM Involve494.fu00 DeathA The EtlE Untitle2 UnbeaB5 LectureE McGraALEKS Re/AppUntitleBb 84752Bb Tak XG p valuA blackboard.wccnet.edu/webapps/assessment/take/launch.jsp?course_assessment_id=5580_1&course_id=_96297_1&content_id=_7095083_1&step=nAppsWCC GatewayAll apps | Microsof...A Winter 2020 MTH..Bb Announcements -.O Launch Meeting -.* Question Completion Status:QUESTION 119 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 grouptook 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 statisticallysignificant difference between the proportion of people willing to take risks in the two groups. Round to 3 decimal places..052QUESTION 2While 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 themajor impact a slight change makes in our calculation. Recalculate the p-value from part 1, but let's pretend that 18 of thetook 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.participants in the high-power groupQUESTION 3Many 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 86of the 100 people in the high-power group in this new research took the gambling risk, and 79 of 100 people in the low-power group took the gambling risk. Performa 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. Roundto 3 decimal places..193QUESTION 4If 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 of100) 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 inquestion 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 toClosSave All AnswersClick Save and Submit to save and submit. Click Save All Answers to save all answers.

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Description: I need help answering #4. Finding p-value 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 grouptook the gambling risk. This new p-value spe

Given that in a sample size of n=200. (100 in each group). Therefore there are total two groups of…

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Statistics

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, therrthe 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 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, therrthe 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.

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Concept explainers

Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.

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Question

I need help answering #4. Finding p-value

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.
QUESTION 3
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 new 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.
.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, therythe p-value would have been much lower than that originally found in
would have been less sensitive and would have provided stronger evidence for the researcher's hypothesis. State the p-value, rounding to
1. This p-v
5 decimal places.
Click Save and Submit to save and submit. Click Save All Answers to save all answers.
Save All Answers
MacBook Air
DII
DD
888
F6
F7
FB
F9
F2
F3
F4
F5
@
$
%

BM Involve
494.fu
00 Death
A The Etl
E Untitle
2 Unbea
B5 Lecture
E McGra
ALEKS Re/App
Untitle
Bb 84752
Bb Tak X
G p valu
A blackboard.wccnet.edu/webapps/assessment/take/launch.jsp?course_assessment_id=5580_1&course_id=_96297_1&content_id=_7095083_1&step=n
Apps
WCC Gateway
All apps | Microsof...
A Winter 2020 MTH..
Bb Announcements -.
O Launch Meeting -.
* Question Completion Status:
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.
.052
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
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.
participants in the high-power group
QUESTION 3
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 new 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.
.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
Clos
Save All Answers
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