MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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You wish to test the following claim (HaHa) at a significance level of α=0.001α=0.001.

      Ho:μ1=μ2Ho:μ1=μ2
      Ha:μ1≠μ2Ha:μ1≠μ2

You obtain the following two samples of data.

Sample #1 Sample #2
50.8 84.4 72.1 78.4
72.9 48.8 87.4 36.1
78.8 51.7 74.7 56.3
65.2 98.6 72.5 72.1
72.9 54.2 69.8 73.4
51.7 68.5 59.4 86.8
48.8 47.6 48.8 85.6
65.2 43.4 76.1 69.8
43.4 69.4 55.6 74.3
108.9 92.4 77.9 46.4
47.6 93.3 60 72.9
74.7 66.6    
72 84.3 66.1 75
86.5 96.6 47.1 79.1
75 74.5 82.2 77.8
79.5 70.9 71.5 104.8
88.8 81.7 99.8 89.3
91.2 87.9 111.1 66.1
68 79.5 82.6 61.4
90.7 115.1 106.9 60.4
50.1 85.7 61.4 100.5
105.8 79.1 88.3 73
68.6 57.1 70.9 67.4
42.4 52.3 80.4 88.8



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

What is the p-value for this sample? For this calculation, use the degrees of freedom reported from the technology you are using. (Report answer accurate to four decimal places.)
p-value = 

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 first population mean is not equal to the second population mean.
  • There is not sufficient evidence to warrant rejection of the claim that the first population mean is not equal to the second population mean.
  • The sample data support the claim that the first population mean is not equal to the second population mean.
  • There is not sufficient sample evidence to support the claim that the first population mean is not equal to the second population mean.
Expert Solution
Check Mark
Step 1 : Introduction

Hypothesis testing :

Hypothesis testing could be a form of applied mathematics reasoning that involves drawing conclusions a couple of population parameter or likelihood distribution victimization knowledge from a sample.
First, a supposition concerning the parameter or distribution is created.
This is called the null hypothesis, and it's denoted by H0.

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