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Quantitative Techniques-II
Notes 2 2 2
x x 70 x x 62 x x 60
Sample variance =
n 1 5 1 , n 1 5 1 , n 1 6 1
70 62 60
2
2
2
s 17.5 s 15.5 s 12
2
1
3
4 4 5
2 n 1 2
i
5. Within column variance s 1
k
n
i
5 1 5 1 6 1
= 17.5 15.5 12
16 3 16 3 16 3
4 4 5
= 17.5 15.5 12
13 13 13
192
Within column variance 14.76
13
Between column variance 20
6. F = 1.354
Within column variance 14.76
7. d.f of Numerator = (3 – 1) = 2.
8. d.f of Denominator = n k = (5 – 1) + (5 – 1) + (6 – 1) = 16 – 3 = 13.
1
9. Refer to table using d.f = 2 and d.f = 13.
10. The value is 3.81. This is the upper limit of acceptance region. Since calculated value 1.354
lies within it we can accept H0, the null hypothesis.
Conclusion: There is no significant difference in the effect of the three training methods.
Self Assessment
Fill in the blanks:
3. For using ANOVA, the data should be ............................. in nature.
4. F test has ............................. parameters.
13.3 Summary
Testing the hypothesis about difference between two means: This can be used when two
population means are given and null hypothesis is H : P1 = P2.
o
ANOVA is a statistical technique. It is used to test the equality of three or more sample
means. Based on the means, inference is drawn whether samples belongs to same
population or not.
13.4 Keywords
ANOVA: It is a statistical technique. It is used to test the equality of three or more sample means.
Based on the means, inference is drawn whether samples belongs to same population or not.
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