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Statistical reliability

Our key aim is to provide statistically reliable information on which both strategic and tactical decisions can be based with confidence.

Sample size has an important role to play in ensuring the findings are representative of the whole population whilst meeting the needs of clients in terms of reliability of data and, of course, budget.

For quantitative research techniques based on statistical reliability the calculation of confidence intervals is used to ensure that the sample is truly representative of the whole. Knowing the reliability of the study means that findings can be defended on the basis of logic rather than emotion.

The box below shows the confidence interval with different sample sizes. By selecting the most appropriate confidence interval (often referred to as the margin of error) you can be certain that the findings cannot be dismissed on grounds of dubious methodology.

Population
Statistical Reliability
+/- 5%
+/-10%
25
24
20
50
44
33
100
80
49
500
217
81
1000
278
88
5000
357
94
For example: a response rate of 81 out of a population of 500 is needed for a +/ 10% confidence interval. If the mean of all the respondents' scores is 4 on a scale of 1 to 5, the actual range will be between 3.6 and 4.4 (on 95% of occasions). At the more rigorous +/ 5% (217 responses) the range narrows to between 3.8 and 4.2.

Updated: 10 December, 2009
 
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