In this problem we will assume that the weight measurements of stroke patients over 80 years old at RWJ hospital are normally distributed with a true standard deviation of 20lb. Compute a 95% CI for the true average weight if the mean of a random sample of 25 stroke patients is 160 lb. Suppose we want to test the null hypothesis that the mean weight of stroke patients over 80 years old is 175 vs the alternative that it is less than 175 pounds. Which test should I use and why?. Follow the test procedure for a 5% significance level and interpret the test result in terms of the mean weight of stroke patients.

Answered: In this problem we will assume that the…

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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In this problem we will assume that the weight measurements of stroke patients over 80 years old at RWJ hospital are normally distributed with a true standard deviation of 20lb.

Compute a 95% CI for the true average weight if the mean of a random sample of 25 stroke patients is 160 lb.
Suppose we want to test the null hypothesis that the mean weight of stroke patients over 80 years old is 175 vs the alternative that it is less than 175 pounds. Which test should I use and why?. Follow the test procedure for a 5% significance level and interpret the test result in terms of the mean weight of stroke patients.

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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