An important problem in statistics is estimating the population mean on the basis of the sample mean. For example, suppose that we want to calculate the average height of the entire American population. It is clearly not feasible to measure the height of each and every person in the country.
The solution to this problem is that we can select a random sample of some people and use the average height of this sample as an estimate for the actual population mean. Of course, since we are using a sample instead of the actual population there is always a scope for error. An important question is how many people should we include in our sample.
The below calculator allows us to calculate the desired sample size. If we specify the acceptable margin of error and the confidence level then we can obtain the required sample size.
Sample Size: 35
The estimate’s degree of uncertainty is described by the estimate’s confidence level. This is the possibility that the true mean is present in the margin of error. The sample size should be larger the higher the confidence level.
The degree of accuracy you need is the margin of error. This is the projected range of values for the true mean. Bigger sample size is necessary for a narrower margin of error.