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 a0.01significance level for both parts. Male BMIFemale BMI μμ1μ2n4343x27.772724.1075s8.1260775.794828 * Find the Tstat* find the p value* State the conclusion* Construct a confidence interval suitable for testing the claim that the two samples are from populations with the same mean.* Does the confidence interval support the conclusion of the test

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Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.5: Comparing Sets Of Data

Problem 13PPS

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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.			Male BMI	Female BMI
μ	μ1	μ2
n	43	43
x	27.7727	24.1075
s	8.126077	5.794828

* Find the Tstat

* find the p value

* State the conclusion

* Construct a confidence interval suitable for testing the claim that the two samples are from populations with the same mean.

* Does the confidence interval support the conclusion of the test

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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