Sample Size Calculator
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Sample Size Terminology
The confidence interval is the plus-or-minus figure usually reported in newspaper or television opinion poll results. For example, if you use a confidence interval of 4 and 47% percent of your sample picks an answer you can be "sure" that if you had asked the question of the entire relevant population between 43% (47-4) and 51% (47+4) would have picked that answer.
The confidence level tells you how sure you can be. 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 researchers use the 95% confidence level.
When you put the confidence level and the confidence interval together, you can say that you are 95% sure that the true percentage of the population is between 43% and 51%.
The wider the confidence interval you are willing to accept, the more
certain you can be that the whole population answers would be within that
range. For example, if you asked a sample of 1000 people in a city which
brand of cola they preferred, and 60% said Brand A, you can be very certain
that between 40 and 80% of all the people in the city actually do prefer
that brand, but you cannot be so sure that between 59 and 61% of the people
in the city prefer the brand.
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(707) 765-1001 surveys@usa.net |
