Saturday, September 8, 2012

September 6- Checking And Review Day


        September 6 is a day where we just check the assignment that we have. But as we check, we are not only after the high points but we are also after the principle or idea behind. Our assignment is about testing the difference between two variances. There are ideas that we always should remember. These are the following:
1.    When finding the critical value for one-tailed test, we just have to know the level of significance, the d.f.N which is obtain by subtracting 1 to the number of sample or n and the d.f.D which is also obtain by subtracting 1 from the n. And finallly, you just need to find the intersection between the d.f.N and the d.f.D.
2.    If it is a two tailed test, we should first split the alpha, and then obtain the d.f.N and d.f.D. Then find the intersection between them.
3.    We should always remember that the larger the variance should be the s21 and placed in the numerator of the formula. In identifying the s21, we should be after the bigger variance not the bigger number of sample.
4.    When P-value method is use, it requires looking through all the F tables using the specific d.f.N and d.f.D values.

Let me give you an example of the problem that we have answered that day.
·         A manager hypothesize that the variance for the number who buys female footwear is greater than the variance for the number who buys male footwear. The data are shown below. Is their enough evidence to support the claim using a=0.01?

    Male                                                    Female
n= 23                                                       n= 19
s21=3.8                                                     s22= 4.6

1.    State the hypothesis
H0: δ21δ22
H1: δ21 > δ22

2.    Find the critical value.
d.f.N=18, d.f.D= 22, C.V= 2.98

            3. Solve for the F-Test
               F= s21/ s22
                   F= 4.6/3.8= 1.21

       4. Make the decision
Do not reject the null hypothesis since 1.21 < 2.98    

            5.  Summarize the results
               There is not enough evidence to support the claim

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