Male BMI Female BMI Given in the table are the BMI statistics for random samples of men and women. Assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. Complete parts (a) and (b) below. Use a 0.01 significance level for both parts. 50 50 27.2413 25.1298 S 7.790143 4.213601 a. Test the claim that males and females have the same mean body mass index (BMI). What are the null and alternative hypotheses? OB. H, =2 H: H H2 OD. Ho H H2 H P2 OC. Hg: H 2H2 The test statistic, t is (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) State the conclusion for the test. OA. Reject the null hypothesis. There is not sufficient evidence to warrant rejection of the claim that men and women have the same mean BMI. B. Fail to reject the null hypothesis. There is not sufficient evidence to warrant rejection of the claim that men and women have the same mean BMI. OC. Reject the null hypothesis. There is sufficient evidence to warrant rejection of the claim that men and women have the same mean BMI. OD. Fail to reject the null hypothesis. There is sufficient evidence to warrant rejection of the claim that men and women have the same mean BMI. b. Construct a confidence interval suitable for testing the claim that males and females have the same mean BMI. (Round to three decimal places as needed) Does the confidence interval support the conclusion of the test? because the confidence interval contains

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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.