100

two data points

First multiply the critical value by the standard deviation. Then divide this result by the error from Step 1. Now square this result. This result is the sample size.

For example, the area between z*=1.28 and z=-1.28 is approximately 0.80. Hence this chart can be expanded to other confidence percentages as well….How to Determine the Minimum Size Needed for a Statistical Sample.

The answer to this is that an appropriate sample size is required for validity. If the sample size it too small, it will not yield valid results. An appropriate sample size can produce accuracy of results. If we are using three independent variables, then a clear rule would be to have a minimum sample size of 30.

A general rule of thumb for the Large Enough Sample Condition is that n≥30, where n is your sample size. You have a moderately skewed distribution, that’s unimodal without outliers; If your sample size is between 16 and 40, it’s “large enough.”

The central limit theorem (CLT) states that the distribution of sample means approximates a normal distribution as the sample size gets larger. Sample sizes equal to or greater than 30 are considered sufficient for the CLT to hold.

There are two schools of thought about sample size – one is that as long as a survey is representative, a relatively small sample size is adequate. Perhaps 300-500 respondents can work. The other point of view is that while maintaining a representative sample is essential, the more respondents you have the better.

Usually, researchers regard 100 participants as the minimum sample size when the population is large. However, In most studies the sample size is determined effectively by two factors: (1) the nature of data analysis proposed and (2) estimated response rate.