Statistical Analysis with R For Dummies
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Working with the standard normal distribution in R couldn’t be easier. The only change you make to the four norm functions is to not specify a mean and a standard deviation — the defaults are 0 and 1.

Here are some examples:

> dnorm(0) [1] 0.3989423 > pnorm(0) [1] 0.5 > qnorm(c(.25,.50,.75)) [1] -0.6744898 0.0000000 0.6744898 > rnorm(5) [1] -0.4280188 -0.9085506 0.6746574 1.0728058 -1.2646055 This also applies to the tigerstats functions:

> pnormGC(c(-1,0),region="between") [1] 0.3413447

> qnormGC(.50, region = "below") [1] 0

To standardize a set of scores so that you can compare them to other sets of scores, you convert each one to a z-score. The formula for converting a score to a z-score (also known as a standard score) is


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Joseph Schmuller, PhD, has taught undergraduate and graduate statistics, and has 25 years of IT experience. The author of four editions of Statistical Analysis with Excel For Dummies and three editions of Teach Yourself UML in 24 Hours (SAMS), he has created online coursework for and is a former Editor in Chief of PC AI magazine. He is a Research Scholar at the University of North Florida.

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