The number of customers served at a busy restaurant on Wednesdays follows a Normal distribution with mean 4,362 and standard deviation 251. Suppose we select a simple random sample of 36 Wednesdays and use it to compute x, the average number of customers served on each of these Wednesdays. What is the probability that the average number of customers served on on these 36 Wednesday exceeds 4,444?

The number of customers served at a busy restaurant on Wednesdays follows a Normal distribution with mean 4,362 and standard deviation 251. Suppose we select a simple random sample of 36 Wednesdays and use it to compute x, the average number of customers served on each of these Wednesdays. What is the probability that the average number of customers served on on these 36 Wednesday exceeds 4,444?

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter13: Probability And Calculus

Section13.2: Expected Value And Variance Of Continuous Random Variables

Problem 10E

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Question

The number of customers served at a busy restaurant on Wednesdays follows a Normal distribution with mean 4,362 and standard deviation 251.

Suppose we select a simple random sample of 36 Wednesdays and use it to compute x, the average number of customers served on each of these Wednesdays. What is the probability that the average number of customers served on on these 36 Wednesday exceeds 4,444?

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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