Library of American University of Madaba
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Albert, Jim.
R by Example Concepts to Code / [electronic resource] : by Jim Albert, Maria Rizzo. - XIII, 359 p. 125 illus., 21 illus. in color. online resource. - Use R! .
Introduction -- Quantitative Data -- Categorical Data -- Presentation Graphics -- Exploratotry Data Analysis -- Basic Inference Models -- Regression -- Analysis of Variance I -- Analysis of Variance II -- Randomiczation tests -- Simulation Experiments -- Bayesian Modeling -- Monte Carlo Methods.
R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, this book is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data and this book is intended to be a useful resource for learning how to implement these procedures in R.
9781461413653
Statistics.
Mathematical statistics.
Statistics.
Statistical Theory and Methods.
QA276-280
519.5
R by Example Concepts to Code / [electronic resource] : by Jim Albert, Maria Rizzo. - XIII, 359 p. 125 illus., 21 illus. in color. online resource. - Use R! .
Introduction -- Quantitative Data -- Categorical Data -- Presentation Graphics -- Exploratotry Data Analysis -- Basic Inference Models -- Regression -- Analysis of Variance I -- Analysis of Variance II -- Randomiczation tests -- Simulation Experiments -- Bayesian Modeling -- Monte Carlo Methods.
R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, this book is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data and this book is intended to be a useful resource for learning how to implement these procedures in R.
9781461413653
Statistics.
Mathematical statistics.
Statistics.
Statistical Theory and Methods.
QA276-280
519.5