In one region, the September energy consumption levels for single-family homes are found to be normally distributed with a mean of 1050 kWh and a standard deviation of 218 kWh. a) Find P95, which is the consumption level separating the bottom 95% from the top 5% b) If 50 different homes are randomly selected, find the probability that the sample mean energy consumption level for September is greater than 1075 kWh.

In one region, the September energy consumption levels for single-family homes are found to be normally distributed with a mean of 1050 kWh and a standard deviation of 218 kWh. a) Find P95, which is the consumption level separating the bottom 95% from the top 5% b) If 50 different homes are randomly selected, find the probability that the sample mean energy consumption level for September is greater than 1075 kWh.

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Description: In one region, the September energy consumption levels for single-family homes are found to be normally distributed with a mean of 1050 kWh and a standard deviation of 218 kWh.a) Find P95, which is the consumption level separating the bottom 95% from

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.4: Distributions Of Data

Problem 19PFA

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Question

In one region, the September energy consumption levels for single-family homes are found to be normally distributed with a mean of 1050 kWh and a standard deviation of 218 kWh.

a) Find P₉₅, which is the consumption level separating the bottom 95% from the top 5%

b) If 50 different homes are randomly selected, find the probability that the sample mean energy consumption level for September is greater than 1075 kWh.

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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