However, if percentages are 51% and 49% respectively, the likelihood of an error is broader.ĭetermining the sample size for a determined accuracy level, you must use the worst possible percentage (50%). If 99% of your sample said “Yes” and 1% “No”, the probability of an error is remote, regardless of the sample size. The accuracy also depends on the percentage of the sample that picks a response in particular. In other words, doubling the sample size, will not reduce at half the margin of error. Nonetheless, this relationship is not linear. This means that for a determined confidence level, the bigger the sample, the smaller the margin of error (or confidence interval). The greater the sample size, the more certain one can be that the responses represent the population. Three factors help determine the confidence of your research: Most researchers use a 95% confidence level.įor instance, if you ask a sample of 1000 people in a city what are their preferences in terms of soda, and 60% claim it’s Brand A, you can be certain that 40% - 80% of people in the city prefer that brand, but you can’t be that certain that 59% - 61% of the people in the city prefer that brand. A confidence level of 95% means you can be 95% certain a confidence level of 99% means you can be 99% certain. The confidence level is how frequently the real percentage of the population would choose a specific answer. To facilitate this process, you can too use our margin of error calculator. The margin of error, also called confidence interval, is the negative or positive number that is generally reported in the outcome of a survey.įor example, if you set the margin of error to 4 and 47% of your sample picks an answer, you can be certain that if you had formulated the question to the entire population, from 43% (47% - 4) to 51% (47% + 4) would have chosen that answer. Now let’s break these concepts down a bit more: The margin of error or confidence interval If you set the sample calculator to a confidence level of 95%, an error margin of 5%, and a total population of 7743955, the sample size would be 385. For instance, Bogotá, Colombia, has 7743955 inhabitants according to the 2018 census.
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