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large sample test |
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| Apr8-11, 11:10 PM | #1 |
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large sample test
can someone give me hint of how to do this question
If the standard deviation of output per acre from a sample of 34 representative firms producing wheat 83 kg ,is the hypothesis that standard deviation of output per acre of all firms producing wheat is 107 kg rejected at 5% level of significance? (large sample test) |
| Apr8-11, 11:57 PM | #2 |
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Has your class covered the F distribution? If so, you are probably meant to square the sample standard deviations to get sample variations and do a hypothesis test on their ratio, as explained by this PDF: http://www.biostat.wisc.edu/~kbroman...th/notes06.pdf
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| Apr9-11, 01:04 AM | #3 |
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Thanks got the point.
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| Apr9-11, 01:12 AM | #4 |
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large sample test
Don't thank me too soon! I was just thinking about this again. The (107)^2 is not a sample variance. It is a hypothesized variance. So I think you use a chi-square test.
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| Apr9-11, 01:24 AM | #5 |
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For sample size N, ((N-1) s^2)/ sigma^2 is distributed as chi squared with N-1 degrees of freedom. s = sample variance.
The title of your post is "large sample test". I don' have any statistical tables handy, so I don't know if you N is too large for a table. |
| Apr9-11, 01:44 AM | #6 |
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I found a recommendation that says for sample sizes > 30 the normal distribution is used to approximate the chi-squared. Compute X^2 = (N-1)s^2/ sigma^2 and find the Z value for a normal random variable from the formula Z = sqrt( 2 X^2) - sqrt(2( N-1)-1 ). The DOC with that info is here:
http://www.google.com/url?sa=t&sourc...F4wmHA&cad=rja |
| Apr10-11, 10:39 PM | #7 |
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I think the Chi-squared test is right, according to the engineering statistics handbook at http://www.itl.nist.gov/div898/handb...on3/eda358.htm
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