For a hypothesis test of the claim that the mean amount of sleep for adults is less than 8 hours, technology output shows that the hypothesis test has power of 0.4574 of supporting the claim that u < 8 hours of sleep when the actual population mean is 7.5 hours of sleep.Interpret this value of the power,then identify the value of beta and, interpret that value. For a hypothesis test of the claim that the mean amount of sleep for adults is less than 8 hours, technology output shows that the hypothesis test has power of0.4574 of supporting the claim that µ< 8 hours of sleep when the actual population mean is 7.5 hours of sleep. Interpret this value of the power, then identify the valueof B and interpret that value.Interpret this value of the power.O A. The chance of recognizing that u< 8 hours is very high when in reality u= 7.5 hours.O B. The chance of failing to recognize that u=7.5 hours is not very high when in reality u= 7.5 hours.O C. The chance of failing to recognize that u < 8 hours is not very high when in reality p= 7.5 hours.O D. The chance of recognizing that u<8 hours is not very high when in reality u= 7.5 hours.

Statistical hypothesis testing as an important method in inferential statistics. In hypothesis…

Answered: For a hypothesis test of the claim that…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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For a hypothesis test of the claim that the mean amount of sleep for adults is less than 8 hours, technology output shows that the hypothesis test has power of 0.4574 of supporting the claim that u < 8 hours of sleep when the actual population mean is 7.5 hours of sleep.

Interpret this value of the power,
then identify the value of beta and, interpret that value.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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