**Probability and Statistics Problem:**Assume that blood pressure readings are normally distributed with a mean of 125 and a standard deviation of 6.4. If 64 people are randomly selected, find the probability that their mean blood pressure will be less than 127. Round to four decimal places.- A. 0.9938- B. 0.0062- C. 0.8615- D. 0.9998**Explanation:**This problem is an application of the Central Limit Theorem. The average of the sample means (for the sample size n = 64) will also be normally distributed. The sample mean will have the same mean (125) but the standard deviation will be the population standard deviation divided by the square root of the sample size ($ \sigma/\sqrt{n} $).

Given , mean (μ)=125standard deviation (σ) = 6.4sample size (n) =64

Assume that blood pressure readings are normally distributed with a mean of 125 and a standard deviation of 6.4. If 64 people are randomly selected, find the probability that their mean blood pressure will be less than 127. Round to four decimal places.

Assume that blood pressure readings are normally distributed with a mean of 125 and a standard deviation of 6.4. If 64 people are randomly selected, find the probability that their mean blood pressure will be less than 127. Round to four decimal places.

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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Estimation

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Question

**Probability and Statistics Problem:**

Assume that blood pressure readings are normally distributed with a mean of 125 and a standard deviation of 6.4. If 64 people are randomly selected, find the probability that their mean blood pressure will be less than 127. Round to four decimal places.

- A. 0.9938
- B. 0.0062
- C. 0.8615
- D. 0.9998

**Explanation:**
This problem is an application of the Central Limit Theorem. The average of the sample means (for the sample size n = 64) will also be normally distributed. The sample mean will have the same mean (125) but the standard deviation will be the population standard deviation divided by the square root of the sample size ($ \sigma/\sqrt{n} $).

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