suppose we are interested in comparing the proport of male students who smoke to the proportion of female students who smoke. We have a random sample of females) that includes two variables: Smoke = "yes" or "no" and Gender = "female (F)" or "male (M)". The two-way table below summarizes the results. Smoke Yes Smoke = No Sample Size Gender = M Gender F Reference: 3-15-NoTech 9 9 51 81 60 90 Describe how to use the data to construct a bootstrap distribution. What value should be recorded for each of the bootstrap samples.

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Suppose we are interested in comparing the proportion of male students who smoke to the proportion of female students who smoke. We have a random sample of 150 students (60 males and 90
females) that includes two variables: Smoke = "yes" or "no" and Gender = "female (F)" or "male (M)". The two-way table below summarizes the results.
Smoke = Yes
Smoke = No
Sample Size
60
90
Gender = M
Gender = F
Reference: 3-15-No Tech
9
9
51
81
Describe how to use the data to construct a bootstrap distribution. What value should be recorded for each of the bootstrap samples.
Transcribed Image Text:Suppose we are interested in comparing the proportion of male students who smoke to the proportion of female students who smoke. We have a random sample of 150 students (60 males and 90 females) that includes two variables: Smoke = "yes" or "no" and Gender = "female (F)" or "male (M)". The two-way table below summarizes the results. Smoke = Yes Smoke = No Sample Size 60 90 Gender = M Gender = F Reference: 3-15-No Tech 9 9 51 81 Describe how to use the data to construct a bootstrap distribution. What value should be recorded for each of the bootstrap samples.
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