The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples. An Introduction to R, you will master the basics of this widely used open-source language, including factors, lists, and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis.
Introduction
♦ What is R?
♦ Why R?
♦ Installing R
♦ R environment
♦ How to get help in R
♦ R Studio Overview
♦ Variables in R
♦ Scalars
♦ Vectors
♦ Matrices
♦ List
♦ Data frames
♦ Cbind, Rbind, attach and detach functions in R
♦ Factors
♦ Getting a subset of Data
♦ Missing values
♦ Converting between vector types
♦ Reading Tabular Data files
♦ Reading CSV files
♦ Importing data from excel
♦ Loading and storing data with a clipboard
♦ Accessing database
♦ Saving in R data
♦ Loading R data objects
♦ Writing data to file
♦ Writing text and output from analyses to file
♦ Selecting rows/observations
♦ Rounding Number
♦ Creating string from a variable
♦ Search and Replace a String or Number
♦ Selecting columns/fields
♦ Merging data
♦ Relabeling the column names
♦ Data sorting
♦ Data aggregation
♦ Finding and removing duplicate records
♦ Apply Function Family
♦ Commonly used Mathematical Functions
♦ Commonly used Summary Functions
♦ Commonly used String Functions
♦ User-defined functions
♦ local and global variable
♦ Working with dates
♦ While loop
♦ If loop
♦ For loop
♦ Arithmetic operations
♦ Box plot
♦ Histogram
♦ Pie graph
♦ Line chart
♦ Scatterplot
♦ Developing graphs
♦ Cover all the current trending packages for Graphs
We can assure a 100% job guarantee and Placement. Contact us for Free - Demo.
Copyright © 2017 - Developed by Infihive Consulting Services LLC changes