Sample size calculator
For most clients the statistical reliability of their market research is of paramount importance. They need to be certain that any plans or strategies that they develop are based on robust data.
So, we often get asked the question: How many interviews do you think I need?
Perhaps the real questions should be: How few interviews can I get away with?
The very simple answer is - it depends on how reliable your data needs to be.
To help you decide you can test out possible interview numbers in the calculator below. You will need to know what your total population is - for example the number of customers if you are doing a customer satisfaction survey or the population of a district, town or ward if you are doing a public consultation.
|How many interviews||How robust is the data|
The confidence interval or the margin of error as it is sometimes called, is the plus-or-minus figure usually reported in newspaper or television opinion poll results. For example, if you use a confidence interval of 5 and 41% percent of your sample give a particular answer you can be "sure" that if you had asked the question of the entire relevant population between 36% (41-5) and 46% (41+5) would have picked that answer.
The confidence level tells you how sure you can be that the answer you receive is representative of the entire population. It is expressed as a percentage and represents how often the true percentage of the population who would pick an answer lies within the confidence interval. The 95% confidence level means you can be 95% certain; the 99% confidence level means you can be 99% certain. Most of our clients use the 95% confidence level.
Accuracy also depends on the percentage of your respondents that pick a particular answer. If 99% of respondents said "Yes" and 1% said "No," the chances of error are remote, irrespective of sample size. However, if the percentages are 51% and 49% the chances of error are much greater. It is easier to be sure of extreme answers than of middle-of-the-road ones.
When determining the sample size needed for a given level of accuracy you must use the worst case percentage (50%). You should also use this percentage if you want to determine a general level of accuracy for a sample you already have.