wikiHow Sample Size Calculator Calculating the sample size depends on various factors, including the size of the population, the level of confidence, and the margin of error. The formula for calculating the sample size is: n = (Z^2 * p * (1 - p)) / e^2 where: * n is the sample size * Z is the z-score or the number of standard deviations from the mean that corresponds to the level of confidence (for example, a 95% confidence level has a z-score of 1.96) * p is the proportion of the population that has a particular characteristic (if unknown, use 0.5 as a conservative estimate) * e is the margin of error, or the maximum distance between the sample mean and the true population mean that is acceptable (expressed as a decimal, such as 0.03 for a 3% margin of error) Here are the steps to calculate the sample size using this formula: 1. Determine the level of confidence required. For example, a confidence level of 95% means that we are 95% certain that the sample mean falls within the confidence interval. 2. Decide on the margin of error that is acceptable. This is typically determined by the level of precision required for the study. 3. Determine the proportion of the population that has the characteristic of interest, if known. 4. Calculate the z-score for the chosen confidence level using a standard normal distribution table or a calculator. 5. Substitute the values into the formula and solve for n. For example, suppose a company wants to determine the average age of its customers with a 95% confidence level and a margin of error of 2 years. The company estimates that the proportion of customers above the age of 40 is 0.6. The z-score for a 95% confidence level is 1.96. Using the formula, we get: n = (1.96^2 * 0.6 * (1 - 0.6)) / (0.02^2) n = 369 Therefore, the sample size required to estimate the average age of the customers with a 95% confidence level and a margin of error of 2 years is 369. Page