Research Methodology - Dr. Krishan K. Pandey
Research Methodology - Dr. Krishan K. Pandey Research Methodology - Dr. Krishan K. Pandey
Sampling Fundamentals 165 (ii) Standard error of proportion of successes bp ⋅ qg n (iii) Standard error of the difference between proportions of two samples: F HG 1 1 σ p p p q 1 − = ⋅ + 2 n n 1 2 where p = best estimate of proportion in the population and is worked out as under: n p + n p p = n + n 1 1 2 2 1 2 q = 1 – p n 1 = number of events in sample one n 2 = number of events in sample two Note: Instead of the above formula, we use the following formula: p1 q1 p q − = + n n σ p p 1 2 when samples are drawn from two heterogeneous populations where we cannot have the best estimate of proportion in the universe on the basis of given sample data. Such a situation often arises in study of association of attributes. 1 2 2 (b) In case of sampling of variables (large samples): (i) Standard error of mean when population standard deviation is known: σ p σ X = n where σ p = standard deviation of population n = number of items in the sample Note: This formula is used even when n is 30 or less. (ii) Standard error of mean when population standard deviation is unknown: where σ X σ s = standard deviation of the sample and is worked out as under σ s = n = number of items in the sample. = σ s n ΣdXi− Xi 2 n − 1 2 I KJ
166 Research Methodology (iii) Standard error of standard deviation when population standard deviation is known: σ σ s = σ p 2 n (iv) Standard error of standard deviation when population standard deviation is unknown: σ σ s where σ s = = σ 2 s n ΣdXi− Xi 2 n − 1 n = number of items in the sample. (v) Standard error of the coeficient of simple correlation: σ r 1 − r = n where r = coefficient of simple correlation n = number of items in the sample. (vi) Standard error of difference between means of two samples: (a) When two samples are drawn from the same population: F HG 2 1 1 σ X X σ i − = p + 2 n n 2 1 2 (If σ p is not known, sample standard deviation for combined samples eσs1⋅ 2j * may be substituted.) (b) When two samples are drawn from different populations: σ σp σ p − = + n n X X 1 2 I KJ 2 d i d i 1 2 1 (If σ p1 and σ p2 are not known, then in their places σ s1 and σ s2 respectively may be substituted.) (c) In case of sampling of variables (small samples): (i) Standard error of mean when σ p is unknown: 2 2
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166 <strong>Research</strong> <strong>Methodology</strong><br />
(iii) Standard error of standard deviation when population standard deviation is known:<br />
σ<br />
σ s<br />
=<br />
σ<br />
p<br />
2 n<br />
(iv) Standard error of standard deviation when population standard deviation is unknown:<br />
σ<br />
σ s<br />
where σ s =<br />
=<br />
σ<br />
2<br />
s<br />
n<br />
ΣdXi− Xi<br />
2<br />
n − 1<br />
n = number of items in the sample.<br />
(v) Standard error of the coeficient of simple correlation:<br />
σ r<br />
1 − r<br />
=<br />
n<br />
where<br />
r = coefficient of simple correlation<br />
n = number of items in the sample.<br />
(vi) Standard error of difference between means of two samples:<br />
(a) When two samples are drawn from the same population:<br />
F<br />
HG<br />
2 1 1<br />
σ X X σ<br />
i − = p +<br />
2 n n<br />
2<br />
1 2<br />
(If σ p is not known, sample standard deviation for combined samples eσs1⋅ 2j<br />
*<br />
may be substituted.)<br />
(b) When two samples are drawn from different populations:<br />
σ<br />
σp σ p<br />
− = +<br />
n n<br />
X X<br />
1 2<br />
I<br />
KJ<br />
2<br />
d i d i<br />
1 2<br />
1<br />
(If σ p1 and σ p2 are not known, then in their places σ s1 and σ s2 respectively may<br />
be substituted.)<br />
(c) In case of sampling of variables (small samples):<br />
(i) Standard error of mean when σ p is unknown:<br />
2<br />
2