Statistically Figuring Sample Size When designing a study, the sample size is an important consideration because the larger the sample size, the more data you have, and the more precise your results will be (assuming high-quality data). If you know the level of precision you want (that is, your desired margin of error), you can calculate the sample size needed to achieve it. To find the sample size needed to estimate a population mean ( µ), use the following formula: In this formula, MOE represents the desired margin of error (which you set ahead of time), and σ represents the population standard deviation. If σ is unknown, you can estimate it with the sample standard deviation, s, from a pilot study; z* is the critical value for the confidence level you need. Checking Out Statistical Confidence Interval Critical Values Critical values ( z *-values) are an important component of confidence intervals (the statistical technique for estimating population parameters). The z *-value, which appears in the margin of error formula, measures the number of standard errors to be added and subtracted in order to achieve your desired confidence level (the percentage confidence you want).

The following table shows common confidence levels and their corresponding z *-values. Confidence Level z*– value 80% 1.28 85% 1.44 90% 1. Harlem Globetrotters The Team That Changed The World there. 64 95% 1.96 98% 2.33 99% 2.58.

Divergent views of probability and statistics. The eminent statistician Karl Pearson. Chapter 1 A Review of Basic Statistical Concepts 3. Duplicate Email Remover Serial 2.17.2. MEDICAL STATISTICS MADE EASY Michael Harris General Practitioner and Lecturer in General Practice, Bath, UK and Gordon Taylor Senior Research Fellow in Medical.