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According to the Bureau of Labor Statistics, the average weekly pay for a U.S. production worker was $441.84. Assume that available data indicate that production worker wages were normally distributed with a standard deviation of $90. What is the probability that a worker earned between $400 and $500

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Answer:

41.94% probability that a worker earned between $400 and $500.

Explanation:

Problems of normally distributed samples can be solved using the z-score formula.

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


Z = (X - \mu)/(\sigma)

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 problem, we have that:


\mu = 441.84, \sigma = 90

What is the probability that a worker earned between $400 and $500?

This is the pvalue of Z when X = 500 subtracted by the pvalue of Z when X = 400. So

X = 500


Z = (X - \mu)/(\sigma)


Z = (500 - 441.84)/(90)


Z = 0.65


Z = 0.65 has a pvalue of 0.7422

X = 400


Z = (X - \mu)/(\sigma)


Z = (400 - 441.84)/(90)


Z = 0.65


Z = -0.46 has a pvalue of 0.3228

So there is a 0.7422 - 0.3228 = 0.4194 = 41.94% probability that a worker earned between $400 and $500.

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