You wish to test the following claim (H1) at a significance level of α=0.005. For the context of this problem, d=x2−x1 where the first data set represents a pre-test and the second data set represents a post-test. Ho:μd=0 H1:μd>0You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain pre-test and post-test samples for n=111 subjects. The average difference (post - pre) is ¯d=3.3 with a standard deviation of the differences of sd=38.5.What is the critical value for this test? (Report answer accurate to three decimal places.)critical value = What is the test statistic for this sample? (Report answer accurate to three decimal places.)test statistic = The test statistic is...in the critical regionnot in the critical regionThis test statistic leads to a decision to...reject the nullaccept the nullfail to reject the nullAs such, the final conclusion is that...There is sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is greater than 0.There is not sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is greater than 0.The sample data support the claim that the mean difference of post-test from pre-test is greater than 0.There is not sufficient sample evidence to support the claim that the mean difference of post-test from pre-test is greater than 0.

Given data : sample size, n = 111 sample mean, x̄ = 3.3 sample standard deviation,s= 38.5 population mean,μ= 0.0 Significance level, α= 0.005Solution : A) Hypothesis test : The null and alternative hypothesis is H0: ud = 0.0 Ha: ud > 0.0 Degree of freedom df=n-1= 111 -1= 110 critical value : critical value at α = 0.005 tα= 2.621 Critical value is 2.621B) Test statistic : The test statistic is 0.903C) Decision rule Reject Ho if t > 2.621 As t < 2.621 we fail to reject the null hypothesis. The test statistic is not in the critical region. D) fail to reject the nullE) There is not sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is greater than 0.

Answered: You wish to test the following claim…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Related questions

Question

You wish to test the following claim (H1) at a significance level of α=0.005. For the context of this problem, d=x2−x1 where the first data set represents a pre-test and the second data set represents a post-test.

Ho:μd=0
H1:μd>0

You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain pre-test and post-test samples for n=111 subjects. The average difference (post - pre) is ¯d=3.3 with a standard deviation of the differences of sd=38.5.

What is the critical value for this test? (Report answer accurate to three decimal places.)
critical value =

What is the test statistic for this sample? (Report answer accurate to three decimal places.)
test statistic =

The test statistic is...

in the critical region
not in the critical region

This test statistic leads to a decision to...

reject the null
accept the null
fail to reject the null

As such, the final conclusion is that...

There is sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is greater than 0.
There is not sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is greater than 0.
The sample data support the claim that the mean difference of post-test from pre-test is greater than 0.
There is not sufficient sample evidence to support the claim that the mean difference of post-test from pre-test is greater than 0.

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 + ...

Expert Solution