A Trucking Company claims that the mean weight for their delivery trucks when they are fully loaded is 7,000 pounds and the standard deviation is 200 pounds. Assume that the population follows a normal distribution and fifty trucks are randomly selected and weighed. Within what limits will 95% of the sample means occur? Sample means between blank1 - Numeric Answer and blank2 - Numeric Answer Round your answer to one decimal place.

A Trucking Company claims that the mean weight for their delivery trucks when they are fully loaded is 7,000 pounds and the standard deviation is 200 pounds. Assume that the population follows a normal distribution and fifty trucks are randomly selected and weighed. Within what limits will 95% of the sample means occur? Sample means between blank1 - Numeric Answer and blank2 - Numeric Answer Round your answer to one decimal place.

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

A Trucking Company claims that the mean weight for their delivery trucks when they are fully loaded is 7,000 pounds and the standard deviation is 200 pounds. Assume that the population follows a normal distribution and fifty trucks are randomly selected and weighed. Within what limits will 95% of the sample means occur?
Sample means between blank1 - Numeric Answer and blank2 - Numeric Answer

Round your answer to one decimal place.

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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