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Table 24 "95% confidence limits" for estimates which are based on SHS sub-samples of various sizes
e.g. an estimate of 55% which is based on a sample of 800
( i.e. the n corresponding to "100%" is 800) has 95% confidence limits of 55% +/- 4.1%-points
( i.e. 50.9% to 59.1%)
Sub-
sample
size.
(i.e the "n="
value corresp onding to 100%) | Estimate |
|---|
5%
or
95% | 10%
or
90% | 15%
or
85% | 20%
or
80% | 25%
or
75% | 30%
or
70% | 35%
or
65% | 40%
or
60% | 45%
or
55% | 50% |
|---|
percentage points ( + / - ) |
100 | 5.1 | 7.1 | 8.4 | 9.4 | 10.2 | 10.8 | 11.2 | 11.5 | 11.7 | 11.8 |
200 | 3.6 | 5.0 | 5.9 | 6.7 | 7.2 | 7.6 | 7.9 | 8.1 | 8.3 | 8.3 |
300 | 3.0 | 4.1 | 4.8 | 5.4 | 5.9 | 6.2 | 6.5 | 6.7 | 6.8 | 6.8 |
400 | 2.6 | 3.5 | 4.2 | 4.7 | 5.1 | 5.4 | 5.6 | 5.8 | 5.9 | 5.9 |
500 | 2.3 | 3.2 | 3.8 | 4.2 | 4.6 | 4.8 | 5.0 | 5.2 | 5.2 | 5.3 |
600 | 2.1 | 2.9 | 3.4 | 3.8 | 4.2 | 4.4 | 4.6 | 4.7 | 4.8 | 4.8 |
700 | 1.9 | 2.7 | 3.2 | 3.6 | 3.8 | 4.1 | 4.2 | 4.4 | 4.4 | 4.4 |
800 | 1.8 | 2.5 | 3.0 | 3.3 | 3.6 | 3.8 | 4.0 | 4.1 | 4.1 | 4.2 |
900 | 1.7 | 2.4 | 2.8 | 3.1 | 3.4 | 3.6 | 3.7 | 3.8 | 3.9 | 3.9 |
1,000 | 1.6 | 2.2 | 2.7 | 3.0 | 3.2 | 3.4 | 3.5 | 3.6 | 3.7 | 3.7 |
1,200 | 1.5 | 2.0 | 2.4 | 2.7 | 2.9 | 3.1 | 3.2 | 3.3 | 3.4 | 3.4 |
1,400 | 1.4 | 1.9 | 2.2 | 2.5 | 2.7 | 2.9 | 3.0 | 3.1 | 3.1 | 3.1 |
1,600 | 1.3 | 1.8 | 2.1 | 2.4 | 2.5 | 2.7 | 2.8 | 2.9 | 2.9 | 2.9 |
1,800 | 1.2 | 1.7 | 2.0 | 2.2 | 2.4 | 2.5 | 2.6 | 2.7 | 2.8 | 2.8 |
2,000 | 1.1 | 1.6 | 1.9 | 2.1 | 2.3 | 2.4 | 2.5 | 2.6 | 2.6 | 2.6 |
2,500 | 1.0 | 1.4 | 1.7 | 1.9 | 2.0 | 2.2 | 2.2 | 2.3 | 2.3 | 2.4 |
3,000 | 0.9 | 1.3 | 1.5 | 1.7 | 1.9 | 2.0 | 2.0 | 2.1 | 2.1 | 2.1 |
3,500 | 0.9 | 1.2 | 1.4 | 1.6 | 1.7 | 1.8 | 1.9 | 1.9 | 2.0 | 2.0 |
4,000 | 0.8 | 1.1 | 1.3 | 1.5 | 1.6 | 1.7 | 1.8 | 1.8 | 1.9 | 1.9 |
5,000 | 0.7 | 1.0 | 1.2 | 1.3 | 1.4 | 1.5 | 1.6 | 1.6 | 1.7 | 1.7 |
6,000 | 0.7 | 0.9 | 1.1 | 1.2 | 1.3 | 1.4 | 1.4 | 1.5 | 1.5 | 1.5 |
7,000 | 0.6 | 0.8 | 1.0 | 1.1 | 1.2 | 1.3 | 1.3 | 1.4 | 1.4 | 1.4 |
8,000 | 0.6 | 0.8 | 0.9 | 1.1 | 1.1 | 1.2 | 1.3 | 1.3 | 1.3 | 1.3 |
9,000 | 0.5 | 0.7 | 0.9 | 1.0 | 1.1 | 1.1 | 1.2 | 1.2 | 1.2 | 1.2 |
10,000 | 0.5 | 0.7 | 0.8 | 0.9 | 1.0 | 1.1 | 1.1 | 1.2 | 1.2 | 1.2 |
12,000 | 0.5 | 0.6 | 0.8 | 0.9 | 0.9 | 1.0 | 1.0 | 1.1 | 1.1 | 1.1 |
14,000 | 0.4 | 0.6 | 0.7 | 0.8 | 0.9 | 0.9 | 0.9 | 1.0 | 1.0 | 1.0 |
16,000 | 0.4 | 0.6 | 0.7 | 0.7 | 0.8 | 0.9 | 0.9 | 0.9 | 0.9 | 0.9 |
18,000 | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.8 | 0.8 | 0.9 | 0.9 | 0.9 |
20,000 | 0.4 | 0.5 | 0.6 | 0.7 | 0.7 | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 |
25,000 | 0.3 | 0.4 | 0.5 | 0.6 | 0.6 | 0.7 | 0.7 | 0.7 | 0.7 | 0.7 |
30,000 | 0.3 | 0.4 | 0.5 | 0.5 | 0.6 | 0.6 | 0.6 | 0.7 | 0.7 | 0.7 |
35,000 | 0.3 | 0.4 | 0.4 | 0.5 | 0.5 | 0.6 | 0.6 | 0.6 | 0.6 | 0.6 |
40,000 | 0.3 | 0.4 | 0.4 | 0.5 | 0.5 | 0.5 | 0.6 | 0.6 | 0.6 | 0.6 |
45,000 | 0.2 | 0.3 | 0.4 | 0.4 | 0.5 | 0.5 | 0.5 | 0.5 | 0.6 | 0.6 |
50,000 | 0.2 | 0.3 | 0.4 | 0.4 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
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