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e short form of the gene. They find that 26 of the subjects in their study have at least one copy of the short form of the gene, fa 0.0668. What is the best interpretation of this p-value? O The probability we would reject the null hypothesis, if in reality the population proportion were 0.26, is 0.0668. The probability we would reject the null hypothesis, if in reality the population proportion were 0.2, is 0.0668. The probability we would find a sample proportion of 0.2 or greater if in reality the populatio

e short form of the gene. They find that 26 of the subjects in their study have at least one copy of the short form of the gene, fa 0.0668. What is the best interpretation of this p-value? O The probability we would reject the null hypothesis, if in reality the population proportion were 0.26, is 0.0668. The probability we would reject the null hypothesis, if in reality the population proportion were 0.2, is 0.0668. The probability we would find a sample proportion of 0.2 or greater if in reality the populatio

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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**Educational Text: Understanding p-value in Genetic Research** A gene can exist in 2 forms: a short form and a long form. In a given population, 20% of people possess at least one copy of the short form of the gene. Researchers hypothesize that having the short form of the gene is associated with diabetes. To investigate this, they hypothesize that more than 20% of all diabetics have at least one copy of the short form. To test this hypothesis, researchers randomly select 100 diabetic individuals and test them for the presence of the short form of the gene. They find that 26 of these individuals have at least one copy of the short form. The resulting *p-value* from this analysis is 0.0668. The question posed is: What is the best interpretation of this *p-value*? Options: - The probability we would reject the null hypothesis, if in reality the population proportion were 0.26, is 0.0668. - The probability we would reject the null hypothesis, if in reality the population proportion were 0.2, is 0.0668. - The probability we would find a sample proportion of 0.2 or greater, if in reality the population proportion were 0.26, is 0.0668. - The probability we would find a sample proportion of 0.26 or greater, if in reality the population proportion were 0.2, is 0.0668. This scenario explores statistical hypothesis testing, allowing researchers to infer the likelihood of an observed result, assuming the null hypothesis (population proportion = 0.2) is true.
Transcribed Image Text:**Educational Text: Understanding p-value in Genetic Research** A gene can exist in 2 forms: a short form and a long form. In a given population, 20% of people possess at least one copy of the short form of the gene. Researchers hypothesize that having the short form of the gene is associated with diabetes. To investigate this, they hypothesize that more than 20% of all diabetics have at least one copy of the short form. To test this hypothesis, researchers randomly select 100 diabetic individuals and test them for the presence of the short form of the gene. They find that 26 of these individuals have at least one copy of the short form. The resulting *p-value* from this analysis is 0.0668. The question posed is: What is the best interpretation of this *p-value*? Options: - The probability we would reject the null hypothesis, if in reality the population proportion were 0.26, is 0.0668. - The probability we would reject the null hypothesis, if in reality the population proportion were 0.2, is 0.0668. - The probability we would find a sample proportion of 0.2 or greater, if in reality the population proportion were 0.26, is 0.0668. - The probability we would find a sample proportion of 0.26 or greater, if in reality the population proportion were 0.2, is 0.0668. This scenario explores statistical hypothesis testing, allowing researchers to infer the likelihood of an observed result, assuming the null hypothesis (population proportion = 0.2) is true.
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