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Mastering Scientific Computing with R

You're reading from   Mastering Scientific Computing with R Employ professional quantitative methods to answer scientific questions with a powerful open source data analysis environment

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783555253
Length 432 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Programming with R 2. Statistical Methods with R FREE CHAPTER 3. Linear Models 4. Nonlinear Methods 5. Linear Algebra 6. Principal Component Analysis and the Common Factor Model 7. Structural Equation Modeling and Confirmatory Factor Analysis 8. Simulations 9. Optimization 10. Advanced Data Management Index

Probability distributions

R makes it very easy to plot and get statistical information on many probability distributions. For those who are not familiar with probability distributions, they are defined as a table or an equation that links each outcome of a statistical experiment with its probability of occurrence. A summary of many common probability distributions available in R is available in the following table:

Probability distribution

R name

Beta

beta

Binomial

binom

Cauchy

cauchy

Chi square

chisq

Exponential

exp

F

f

Gamma

gamma

Geometric

geom

Hypergeometric

hyper

Logistic

logis

Lognormal

lnorm

Negative Binomial

nbinom

Normal

norm

Poisson

pois

Student t

t

Uniform

unif

Tukey

tukey

Weibull

weib

Wilcoxon

wilcox

You can also get this summary in R by entering help("distributions"). For additional probability distributions, and the packages needed to load them, you can consult the CRAN distributions page at http://cran.r-project.org/web/views...

You have been reading a chapter from
Mastering Scientific Computing with R
Published in: Jan 2015
Publisher:
ISBN-13: 9781783555253
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