Testing of the hypothesis of variance

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The discussion revolves around testing the hypothesis that the variance of IQ scores for a sample of professors differs from the general population's variance. The null hypothesis (H0) states that the standard deviation is 15, while the alternative hypothesis (H1) posits that it is not equal to 15. A chi-square test statistic of 10.22 was calculated, with a critical value of 38.076 at a 0.05 significance level. Participants clarified that the focus is on variance rather than mean IQ, emphasizing that the mean of the general population does not affect the variance test. The conversation highlights the importance of correctly defining hypotheses and understanding the implications of the test being conducted.
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Homework Statement


for randomly selected IQ adult scores are normally distributed with mean of 100 and standarrd deviation of 15 ,. a sample of 24 randomly selected professors resulted in the IQ scores having a standard deviation of 10 . Test the claim that the IQ scores for the professors is same as the general population of 1.5 . Use 0.05 significance of level

Homework Equations

The Attempt at a Solution



H0 = standard deviation = 15

H0 = standard deviation not equal to 15

So , chi square test = (24-1)(10^2) / (15^2) = 10.22

From table , critical chi square value = 38.076 I am not sure to reject or accept the H0 , since this is 2 tailed test . I was told that for chi square test , there's only one tailed test exist
 
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tzx9633 said:

Homework Statement


for randomly selected IQ adult scores are normally distributed with mean of 100 and standarrd deviation of 15 ,. a sample of 24 randomly selected professors resulted in the IQ scores having a standard deviation of 10 . Test the claim that the IQ scores for the professors is same as the general population of 1.5 . Use 0.05 significance of level

Homework Equations

The Attempt at a Solution



H0 = standard deviation = 15

H0 = standard deviation not equal to 15

So , chi square test = (24-1)(10^2) / (15^2) = 10.22

From table , critical chi square value = 38.076 I am not sure to reject or accept the H0 , since this is 2 tailed test . I was told that for chi square test , there's only one tailed test exist

You have written two different things for the same symbol "H0". Can I suppose one of them is H1? If the second one is H1, you need to be more careful about whether to take it to be "##\neq 15##", "## < 15##" or "## > 15##". Those three different possible H1s will produce 3 different significant tests.
 
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Ray Vickson said:
You have written two different things for the same symbol "H0". Can I suppose one of them is H1? If the second one is H1, you need to be more careful about whether to take it to be "##\neq 15##", "## < 15##" or "## > 15##". Those three different possible H1s will produce 3 different significant tests.
Yes , sorry for my mistake .

H0 = standard deviation = 15

H1 = standard deviation not equal to 15

So , chi square test = (24-1)(10^2) / (15^2) = 10.22

From table , critical chi square value = 38.076 I am not sure to reject or accept the H0 , since this is 2 tailed test . I was told that for chi square test , there's only one tailed test exist

Can you help me on this ?
 
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tzx9633 said:
Yes , sorry for my mistake .

H0 = standard deviation = 15

H1 = standard deviation not equal to 15

So , chi square test = (24-1)(10^2) / (15^2) = 10.22

From table , critical chi square value = 38.076 I am not sure to reject or accept the H0 , since this is 2 tailed test . I was told that for chi square test , there's only one tailed test exist

Can you help me on this ?

Please stop using a bold font; it looks like you are yelling at us.
Mod edit: I removed the extra bolding in this and the previous posts.
Anyway, all you need is given in http://www.itl.nist.gov/div898/handbook/eda/section3/eda358.htm
 
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tzx9633 said:

Homework Statement


for randomly selected IQ adult scores are normally distributed with mean of 100 and standarrd deviation of 15 ,. a sample of 24 randomly selected professors resulted in the IQ scores having a standard deviation of 10 . Test the claim that the IQ scores for the professors is same as the general population of 1.5 . Use 0.05 significance of level


I am confused: are you testing for IQ or for variance in the distribution? don't you mean "Test the claim that the standard deviation for professors is the same as that for the general population"?
 
tzx9633 said:
Test the claim that the IQ scores for the professors is same as the general population of 1.5
The figure 1.5 is a typo. It should be 15, which is what was used in the calculation.

WWGD said:
I am confused: are you testing for IQ or for variance in the distribution? don't you mean "Test the claim that the standard deviation for professors is the same as that for the general population"?
I'm pretty sure that what you wrote is what he meant; i.e., the test is for the standard deviation of IQ scores of this subpopulation.
 
Mark44 said:
The figure 1.5 is a typo. It should be 15, which is what was used in the calculation.

I'm pretty sure that what you wrote is what he meant; i.e., the test is for the standard deviation of IQ scores of this subpopulation.
But then one thing that is confusing is the mention of IQ of the general population, when what is being tested is the variance. The profs' IQ may also be different, but the general pop's IQ being 100 is never used and has no effect on the results.
 
WWGD said:
But then one thing that is confusing is the mention of IQ of the general population, when what is being tested is the variance. The profs' IQ may also be different, but the general pop's IQ being 100 is never used and has no effect on the results.
The implicit assumption that is behind the null hypothesis is that the distrubutions of the professors' IQs is the same as the population. In the problem in this thread, the goal is to test whether the variance of the professors' IQs is the same as that of the general population. The mean isn't used in a ##\chi ^2## test.
 
WWGD said:
But then one thing that is confusing is the mention of IQ of the general population, when what is being tested is the variance. The profs' IQ may also be different, but the general pop's IQ being 100 is never used and has no effect on the results.

Right, and not only that, the "professor" group may have a different mean IQ as well. As long as the professors' sample mean is used when computing the professors' sample variance, that will not matter at all (assuming normality, of course).
 
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