Anmerkungen:
Distributed to the book trade worldwide by Springer Science + Business Media
Beschreibung:
R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. 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. 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. --
R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. 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. 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. --