Using R for Statistics
- 2h 58m
- Sarah Stowell
- Apress
- 2014
R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. If you need to use a variety of statistics, then Using R for Statistics will get you the answers to most of the problems you are likely to encounter.
Using R for Statistics is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations. You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and customize their appearance, perform hypothesis tests such as the t-tests and analyses of variance, and build regression models. Examples are built around actual datasets to simulate real-world solutions, and programming basics are explained to assist those who do not have a development background.
After reading and using this guide, you'll be comfortable using and applying R to your specific statistical analyses or hypothesis tests. No prior knowledge of R or of programming is assumed, though you should have some experience with statistics.
What you’ll learn
- How to apply statistical concepts using R and some R programming
- How to work with data files, prepare and manipulate data, and combine and restructure datasets
- How to summarize continuous and categorical variables
- What is a probability distribution
- How to create and customize plots
- How to do hypothesis testing
- How to build and use regression and linear models
About the Author
Sarah Stowell is a Contract Statistician with Mitsubishi Pharma Europe and has been a Statistician with MDSL International and GlaxoSmithKline previously. She holds a Master of Science degree in Statistics.
In this Book
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R Fundamentals
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Working with Data Files
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Preparing and Manipulating Your Data
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Combining and Restructuring Datasets
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Summary Statistics for Continuous Variables
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Tabular Data
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Probability Distributions
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Creating Plots
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Customizing Your Plots
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Hypothesis Testing
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Regression and General Linear Models
