R Programming

Overview:

Introduction

You will learn how to successfully program in R and how to use R for data analysis. You'll learn how to introduce and organize programming required for a factual programming scenario as well as how to illustrate traditional programming language concepts as they are used in a high-level measurable language. The course addresses practical concerns in factual inference, including programming in R, adding data to R, getting to R bundles, creating R capacity, troubleshooting, profiling R code, and sorting and noting R code. Working models will be provided by themes in the assessment of quantifiable information.

Course Objectives

At the end of this course the participants will be able to:

• Utilize R profiler to gather data point by point.
• Configure programming with facts.
• Make use of the research tools and R circle works.
• Know the fundamental concepts of programming languages.

Targeted Audience

• Programmers
• Anyone interested in R programming

Course Outline

Unit 1: Introducing R: What is it and how to get it

• Starting Out: Becoming Familiar with R
• Starting Out: Working with Objects

Unit 2: Data: Descriptive Statistics and Tabulation

• Data: Distribution
• Simple Hypothesis Testing

Unit 3: Introduction to Graphical Analysis

• Formula Notation and Complex Statistics
• Manipulating Data and Extracting Components

Unit 4: Regression (Linear Modeling)

• More About Graphs
• Writing Your Own Scripts: Beginning to Program

Unit 5:

• Revision
• Workshop