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Introduction to R for Data Analysis

R is a functional programming environment for business analysts and data scientists. It's a language that many non-programmers can easily work with, naturally extending a skill set that is common to high-end Excel users. It's the perfect tool for when the analyst has a statistical, numerical, or probabilities-based problem based on real data and they've pushed Excel past its limits.

Description

Overview

This course covers the fundamentals of the R programming language with the focus on using R for statistical data analysis. It includes hands on labs allowing the students to reinforce the programming concepts by creating practical code example of analyzing data using R.

Who Should Attend

No prior knowledge of statistical data analysis or of the R language is assumed. This course is perfect for those interested using the R language to perform the work of a data scientist, answering important business questions by applying a statistical analysis approach to data.

Course Outline

Module 1: Getting Started with R

  • What is R and Where to Get It
  • Development Tools for R
  • Entering R Expressions

Module 2: R Language Fundamentals

  • Variables
  • Operators
  • Logical Flow
  • Vectors
  • Functions
  • Scripts

Module 3: Extending R

  • Base R Packages
  • Installing R Packages
  • Loading and Unloading Modules
  • Removing Packages

Module 4: Working with Data

  • Date Objects
  • Rectangular Data Objects
  • Data Frames
  • Getting Data Into R
  • Working with External Data

Module 5: Data Analytics

  • Summarizing Data
  • Descriptive Statistics
  • Measuring Variance
  • The Standard Deviation
  • Predictive Analysis

Module 6: Visualizing Your Data

  • About Graphical Analysis
  • Line, Pie and Bar Charts
  • Box-Whisker, Scatter, Pairs, and Dot Plots

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