Hypothesis Testing of Mean & Variance
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The Computer Anxiety Rating Scale (CARS) measures an individual's level of computer anxiety, on a scale from 20 ( no anxiety) to 100 (highest level of anxiety). Researchers at Miami University administered CARS to 172 business students. One of the objectives of the study was to determine whether there is a difference between the level of computer anxiety experienced by female students and male students. They found the following:
Males Females
(sample mean) X: 40.26 36.85
S 13.35 9.42
n 100 72
a) at the 0.05 level of significance, is there evidence of a difference in the variability of the computer anxiety experienced by males and females?
b) Interpret the P-Value
c) What assumption do you need to make about the two populations in order to justify the use of the F test?
d) Based on (a) and (b) which t test defined in section 10.1 should you use to test whether there is a significant difference in mean computer anxiety for female and male students?
Determine the upper tail critical values of F in each of the following two-tailed tests:
Α) α= 0.10, n1 = 16,n2= 21
B)α = 0.05, n1= 16,n2= 21
C) α= 0.01, n1= 16, n2= 21
Assume that you have a sample of n1=8, with the sample mean of x1=42, and a sample standard deviation of s1=4, and you have an independent sample of n2=15 from another population with a sample mean of X2=34 and a sample mean of S2=5.
A) What is the value of the pooled-variance t stat test statistic for testing the null Ho= μ1= μ2?
B) In finding the critical value t α/2, how many degrees of freedom are there?
C) Using the level of siginificance ) α=0.01, what is the critical value for a one-tail test of the hypothesis Ho: μ1 is <( or equal to) μ2 against the alternative H1= : μ1 is >( or equal to) μ2?
D) What is your statistical decision?
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Solution Summary
The solution provides step by step method for the calculation of testing of hypothesis. Formula for the calculation and Interpretations of the results are also included. Interactive excel sheet is included. The user can edit the inputs and obtain the complete results for a new set of data.
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