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