Let x be a random variable that represents white blood cell count per cubic millimeter of whole blood. Assume that x has a distribution that is approximately normal with mean of 7500 and estimated standard deviation of 1750. A test result of x<3500 is an indication of leukopenia. This indicates bone marrow depression that may be the result of a viral infection.What is the probability that on a single test x<3500?Suppose that a doctor uses the average for two tests taken a week apart. What can we say about the probability distribution of ? What is the probability that <3500?Repeat part b with n = 3 tests taken a week apart.Compare your answers for parts a, b, and c. How did the probabilities change as n increased? If a person had <3500 based on three tests, what conclusion would you draw as a doctor or a nurse?

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Answered: Let x be a random variable that…

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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Let x be a random variable that represents white blood cell count per cubic millimeter of whole blood. Assume that x has a distribution that is approximately normal with mean of 7500 and estimated standard deviation of 1750. A test result of x<3500 is an indication of leukopenia. This indicates bone marrow depression that may be the result of a viral infection.

What is the probability that on a single test x<3500?
Suppose that a doctor uses the average for two tests taken a week apart. What can we say about the probability distribution of ? What is the probability that <3500?
Repeat part b with n = 3 tests taken a week apart.
Compare your answers for parts a, b, and c. How did the probabilities change as n increased? If a person had <3500 based on three tests, what conclusion would you draw as a doctor or a nurse?

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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