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Sample Size Determination

  • If you plan to use inferential statistics (e.g., t-tests, ANOVA, etc.) to analyze your evaluation results, you should first conduct a power analysis to determine what size sample you will need. This page describes what power is as well as what you will need to calculate it.
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  • Calculate the number of respondents needed in a survey using our free sample size calculator. Our calculator shows you the amount of respondents you need to get statistically significant results for a specific population. Discover how many people you need to send a survey invitation to obtain your required sample. You can also calculate the margin of error based on your sample size.

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  • Determining the right sample size in a reliability test is very important. If the sample size is too small, not much information can be obtained from the test in order to draw meaningful conclusions; on the other hand, if it is too large, the information obtained through the tests will be beyond that needed, thus time and money are wasted. This tutorial explains several commonly used approaches for sample size determination.
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  • Presentation that covers: the significance of sample size, determination of sample size, factors that may affect sample size, and how to use sample size in a research or study.
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  • Presentation that applies the topics of power and sample size to examples in epigenetic epidemiology studies. Step by step solutions using statistical softwares G*Power and STATA are given.
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  • The process of sample size calculations, including relevant definitions, is explained and clear examples for different study designs are provided for illustration. A range of software packages and websites are discussed and evaluated
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  • Chapter from a textbook that covers the topic of sample size by giving a thorough background and then covering issues that are involved when determining the sample size.
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  • An animated video for use in a biostatistics or consulting class to spark a discussion about collaborative research. The animation was created using the free software available at www.xtranormal.com and distributed here with permission for non-profit use by statistics teachers in their classes or course websites. The script for the animation was written August 4, 2010 by xtranormal user "JosiesJavaMoma". Requests for commercial use should be directed to xtranormal.com
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  • A cartoon to use in teaching about the dangers of extrapolation in the context of predicting the future. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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  • An important idea in statistics is that the amount of data matters. We often teach this with formulas --- the standard error of the mean, the t-statistic, etc. --- in which the sample size appears in a denominator as √n. This is fine, so far as it goes, but it often fails to connect with a student's intuition. In this presentation, I'll describe a kinesthetic learning activity --- literally a random walk --- that helps drive home to students why more data is better and why the square-root arises naturally and can be understood by simple geometry. Students remember this activity and its lesson long after they have forgotten the formulas from their statistics class.

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