Test the claim about the population mean μ at the level of significance α. Assume the population is normally distributed. Claim: μ>19; α=0.05; σ=1.2 Sample statistics: x=19.3, n=50 A. Reject H0.There is enough evidence at the 5% level of significance to support the claim. B. Fail to reject H0.There is not enough evidence at the 5% level of significance to support the claim. C. There is not enough information to decide.

Test the claim about the population mean μ at the level of significance α. Assume the population is normally distributed. Claim: μ>19; α=0.05; σ=1.2 Sample statistics: x=19.3, n=50 A. Reject H0.There is enough evidence at the 5% level of significance to support the claim. B. Fail to reject H0.There is not enough evidence at the 5% level of significance to support the claim. C. There is not enough information to decide.

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

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.1: Measures Of Center

Problem 9PPS

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Question

Test the claim about the population mean μ at the level of significance α.
Assume the population is normally distributed.

Claim: μ>19; α=0.05; σ=1.2

Sample statistics: x=19.3, n=50

Reject H0.There is enough evidence at the 5% level of significance to support the claim.

Fail to reject H0.There is not enough evidence at the 5% level of significance to support the claim.

There is not enough information to decide.

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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