Porphyrin is a pigment in blood protoplasm and other body fluids that is significant in body energy and storage. Let x be a random variable that represents the number of milligrams of porphyrin per deciliter of blood. In healthy circles, x is approximately normally distributed with mean µ = 43 and standard deviation σ = 15. Find the following probabilities. (Round your answers to four decimal places.) a. x is less than 60
b. x is greater than 16
c. x is between 16 and 60
d. x is more than 60

a) 0.8708 = 87.08% probability that x is less than 60

b) 0.9641 = 96.41% probability that x is greater than 16.

c) 0.8349 = 83.49% probability that x is between 16 and 60

d) 0.1292 = 12.92% probability that x is more than 60.

Step-by-step explanation:

When the distribution is normal, we use the z-score formula.

In a set with mean and standard deviation , the zscore of a measure X is given by:

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

In this question, we have that:

a. x is less than 60

This is the pvalue of Z when X = 60. So

has a pvalue of 0.8708

0.8708 = 87.08% probability that x is less than 60

b. x is greater than 16

This is 1 subtracted by the pvalue of Z when X = 16. So

has a pvalue of 0.0359

1 - 0.0359 = 0.9641

0.9641 = 96.41% probability that x is greater than 16.

c. x is between 16 and 60

This is the pvalue of Z when X = 60 subtracted by the pvalue of Z when X = 16. We found those in a and b, si:

0.8708 - 0.0359 = 0.8349

0.8349 = 83.49% probability that x is between 16 and 60

d. x is more than 60

This is 1 subtracted by the pvalue of Z when X = 60.

So

1 - 0.8708 = 0.1292

0.1292 = 12.92% probability that x is more than 60.

c - they will have the same distribution

step-by-step explanation:

this is the only one that could make sense. : )