Code: DSC200
Duration in days: 3
Download: Infosheet
€ 1499

Course R Programming

26-09 till 28-09-2018
28-11 till 30-11-2018
14-01 till 16-01-2019
18-03 till 20-03-2019
20-05 till 22-05-2019
Your starting date

Audience Course R Programming

Course R Programming Big Data analysts and scientists who want to use R for the generation of statistical analyses.

Prerequisites Course R Programming

General knowledge of statistics is required. Programming experience is beneficial for a good understanding.

Realization Training R Programming

The theory is treated on the basis of presentation slides. The concepts are illustrated with demos. R-Studio is used as a development environment. The theory is interspersed with exercises. The course times are from 9.30 to 16.30.

Certification R Programming

The participants will receive an official certificate R Programming after successful completion of the course.

Contents Course R Programming

In this course you will learn how to program in the R language and how to use R for effective data analysis and visualization. R is becoming a standard platform for data analysis and graphics and is able to perform an enormous range of statistical procedures not available in other statistical programs. You will learn how to install and configure R and you will learn the data types of R like vectors, arrays, matrices, lists, data frames and factors. Attention is paid to the use of R library functions and the creation of user defined functions. Control flow in R with the family of apply functions is treated as well. The course then covers statistical analysis models like linear and non-linear models, variable transformations and regressions and reading and manipulation of data in R. Finally attention is paid to R packages and to the use of graphics and plotting in R. Topics in statistical data analysis will provide working examples.

Module 1 : Intro R

Module 2 : Data Types

Module 3 : Functions

Overview of R
History of R
Installing R
The R Community
R Development
R Console
Input and Evaluation
R Syntax
R Objects
Using R Packages
Single Mode Data Structures
Multi Mode Data Structures
R Objects
R Attributes
Data Frames
Dates and Times
Names Attribute
Missing Values
Tabular Data
Using R Functions
Functions for Numeric Data
Logical Data
Missing Data
Character Data
Writing Functions
Scoping Rules
Symbol Binding
Errors and Warnings
Checking Inputs
The Ellipsis
Checking Multivalue Inputs
Using Input Definition

Module 4 : Control Flow

Module 5 : R Models

Module 6 : Data Handling

For loops
While loops
Next, Break
Repetitive Tasks
Family of apply Functions
apply Function
lapply Function
sapply Function
tapply Function
Statistical Models in R
Simple Linear Models
Assessing a Model in R
Multiple Linear Regression
Interaction Terms
Factor Independent Variables
Variable Transformations
R and Object Orientation
Generalized Linear Models
Nonlinear Models
Survival Analysis
Time Series Analysis
R Datasets
Importing CSV Files
Relational Databases
Working with Text Files
Working with Excel
Duplicate Values
Data Aggregation

Module 7 : Packages

Module 8 : Graphics and Plotting

Why R Packages?
Package Structure
Code Quality
Automated Documentation
Extending R Packages
Developing a Test Framework
Including Data in Packages
Including a User Guide
Simulation and Profiling
The str Function
Graphics Devices and Colors
High-Level Graphics Functions
Low-Level Graphics Functions
Graphical Parameters
Controlling the Layout
Simulating a Linear Model
Random Sampling
Quick Plots and Basic Control
Changing Plot Types
Custom Plots
Themes and Layout

SpiralTrain BV

Gebouw "De Sijnsmeester"
Standerdmolen 8 – 1.11
3995 AA Houten

IP Computer Training Centrum
Diemerhof 32-36
1112 XN Diemen

020 7600027

Compu Act Opleidingen
Slinge 303
3085 ER Rotterdam

023 - 551 3409

Kleine Singel 33
3572 CG Utrecht

030 - 737 05 81

IP Computer Training Centrum
Leenderweg 292
5644 AE Eindhoven

040 - 256 65 20