You will learn how to use R tools to do data visualization, data transformation and exploratory data analysis. “R for Data Science” is available free online athttp://r4ds.had.co.nz/. Some other free online courses and books are listed below: Datacamphas a free R tutorial athttps://www...
First Look at The Data – The Structure Let’s load in the data. (By the way, the data below is totally contrived)You can find the datasets for this company here. Feel free to use these datasets for the tutorial. # Load an R data frame. MFG10YearTerminationData <- read.csv("~/Vi...
Review of Doing Bayesian data analysis: A tutorial using R and BUGS.Andrews, Marks
The support for Machine Learning Server will end on July 1, 2022. For more information, see What's happening to Machine Learning Server?Applies to: Microsoft R Client, Machine Learning ServerThis tutorial builds on what you learned in the previous data import and exploration tutorial by adding ...
Cluster Analysis using R One-way ANOVA using R Two-way ANOVA using R Paired sample t-test using R Random Forest in R The postChi-Square test using Rappeared first onStatistical Aid: A School of Statistics. Toleave a commentfor the author, please follow the link and comment on their blog...
Functions are a central concept in nearly every modern programming language, including popular programming languages in data science, such as Python, Julia, and, obviously, R. In this tutorial, we will explore what R functions are and how you can use them. By covering the purpose, syntax, an...
We feel very fortunate to be able to obtain the software application R for use in this book. R has been in active, progressive development by a team of top-notch statisticians for several years. It has matured into one of the best, if not the best, sophisticated data analysis programs ...
In this tutorial I will use the R packagesSemiPar, qgraphandHmiscin addition to the basic packages loaded when R is started. The code is as follows: ### #data from package SemiPar; dataset milan.mort #dataset has 3652 cases and 9 vars ### install.packages(“SemiPar”) ...
Step-wise approach to data analysis. Contribute to aayush26/Data-Analysis development by creating an account on GitHub.
library(rminer)# ctreeB2=fit(schoolsup~.,math[,c(inputs,bout)],model="ctree")# rpartB1=fit(schoolsup~.,math[,c(inputs,bout)],model="rpart")B3=fit(schoolsup~.,math[,c(inputs,bout)],model="mlpe")B4=fit(schoolsup~.,math[,c(inputs,bout)],model="ksvm")C3=fit(Mjob~.,c...