You wish to test the following claim (HaHa) at a significance level of α=0.01α=0.01. For the context of this problem, μd=PostTest−PreTestμd=PostTest-PreTest where the first data set represents a pre-test and the second data set represents a post-test. (Each row represents the pre and post test scores for an individual. Be careful when you enter your data and specify what your μ1μ1 and μ2μ2 are so that the differences are computed correctly.) Ho:μd=0Ho:μd=0 Ha:μd≠0Ha:μd≠0 You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain the following sample of data: pre-test post-test 49.5 47 35.7 37.6 54.8 57.5 54.2 57.2 39.7 44.2 39.7 42.1 42.1 46.4 46.5 46.8 54.8 60 49.7 52.4 35 36.4 61.6 64.3 37.5 36.8 61.1 68.8 56.9 57.5 49.5 59.3 30.5 31.5 62.3 72.8 What is the test statistic for this sample? test statistic = (Report answer accurate to 4 decimal places.) What is the p-value for this sample? p-value = (Report answer accurate to 4 decimal places.) The p-value is... less than (or equal to) αα greater than αα 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 not equal to 0. There is not sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is not equal to 0. The sample data support the claim that the mean difference of post-test from pre-test is not equal to 0. There is not sufficient sample evidence to support the claim that the mean difference of post-test from pre-test is not equal to 0.

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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You wish to test the following claim (HaHa) at a significance level of α=0.01α=0.01. For the context of this problem, μd=PostTest−PreTestμd=PostTest-PreTest where the first data set represents a pre-test and the second data set represents a post-test. (Each row represents the pre and post test scores for an individual. Be careful when you enter your data and specify what your μ1μ1 and μ2μ2 are so that the differences are computed correctly.)

Ho:μd=0Ho:μd=0
Ha:μd≠0Ha:μd≠0

You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain the following sample of data:

pre-test	post-test
49.5	47
35.7	37.6
54.8	57.5
54.2	57.2
39.7	44.2
39.7	42.1
42.1	46.4
46.5	46.8
54.8	60
49.7	52.4
35	36.4
61.6	64.3
37.5	36.8
61.1	68.8
56.9	57.5
49.5	59.3
30.5	31.5
62.3	72.8

What is the test statistic for this sample?
test statistic = (Report answer accurate to 4 decimal places.)

What is the p-value for this sample?
p-value = (Report answer accurate to 4 decimal places.)

The p-value is...

less than (or equal to) αα
greater than αα

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

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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