# Posts Tagged ‘ power ’

## Power and Sample Size Analysis: Z test

October 17, 2012
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This article provide a brief background about power and sample size analysis. Then, power and sample size analysis is computed for the Z test. Continue reading →

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## Power Analysis and the Probability of Errors

September 22, 2012
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$Power Analysis and the Probability of Errors$

Power analysis is a very useful tool to estimate the statistical power from a study. It effectively allows a researcher to determine the needed sample size in order to obtained the required statistical power. Clients often ask (and rightfully so) what the sample size should be for a proposed project. Sample sizes end up being

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## Demonstrating the Power of F Test with gWidgets

April 2, 2010
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e know the real distribution of the F statistic in linear models — it is a non-central F distribution. Under H0, we have a central F distribution. Given 1 – α, we can compute the probability of (correctly) rejecting H0. I created a simple demo to illustrate how the power changes as other parameters vary,

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## R Tips in Stat 511

March 22, 2010
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$\reverse C(X'X)^{-1}X'$

Here are some (trivial) R tips in the course Stat 511. I’ll update this post till the semester is over. Formatting R Code Reading code is pain, but the well-formatted code might alleviate the pain a little bit. The function tidy.source() in the animation package can help us format our R code automatically. By default

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## Design of Experiments – Power Calculations

November 18, 2009
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Prior to conducting an experiment researchers will often undertake power calculations to determine the sample size required in their work to detect a meaningful scientific effect with sufficient power. In R there are functions to calculate either a minimum sample size for a specific power for a test or the power of a test for

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