R is a programming language designed for processing, analyzing and visualizing data. But do not think of R as a replacement for Excel! Instead think of R as another tool that will enable you to work on bigger and complex projects.

The focus of this course will be on data manipulation: importing, manipulating, transforming, combining and summarizing.

If you are experiencing any of the below scenarios, then this course is for you:

• Excel does not handle big data sets well
• Excel does not do well with complex/unstructured data
• Excel does not offer robust statistical functionality
  

Students will need to be familiar with data analysis in excel.

Students who complete this course will be able to use R to help them get the best out of Excel and their data.

Module 1: Introduction and Set-Up

• Dowloading the Software
• Navigating the Software
  
• Using Other Software
  
• Libraries
  
• Getting Help
  

Module 2: Programming Basics

• Assigning Variables
• Comparison Operators
  
• Data Structures
  
• Special Values
  

Module 3: Quick Start (Analysis Examples)

• General Data Analysis
• Using SQL in R
  
• Multiple Regression Model
  

Module 4: Cells are Vectors

• Individual Cells
• Cell Ranges
  
• Working with Vectors
  
• Access Values of a Vector
  
• How Vector Operations Work
  
• Recycling
  

Module 5: Formulas are Functions

• Inputs
• Outputs
• Some base Functions

Module 6: Import and Create Data Sets

• Importing from .csv files
• Importing from .xlsx files
  
• Creating a Data Frame
  
• Deleting a Data Frame
  

Module 7: Inspecting Your Data

• Print first few rows and columns
• Print an arbitrary subset
• Printing all rows or all columns
• Using head() and tail() functions
• Using the view() function
• Structure (str) of the Data Frame
• Print column names() of the Data Frame
• Get certain column names
• Print summary() of the table (partial)
• See unique() values of a column
• Visually understand the Data

Module 8 : Working with Columns

• Refer to Columns
• Create Columns
• Reformat Columns
• Converting strings to numbers with as numeric()
• Rename Columns
• Remove Columns
• Unbound Columns

Module 9: Working with Rows

• Filtering with brackets
• Filtering with subset()
• Filtering uniques with unique()
• Sorting with order()

Module 10: Manipulating Rows and Columns with dplyr

• Select() to select columns
• Mutate()
• Filter() for filtering rows
• Arrange() for sorting rows
• Rename() for renaming columns
• Application: by-group processing with dplyr
• Chaining

Module 11: Shape your Dataset

• Combine Data Tables
• PivotTables – Summarize and Transpose your Data

Module 12: Working with Lists

• What is a list?
• Two common uses
  
• How to get things from lists
  
• Creating and modifying lists
  
• Basic list functions
  

Module 13: Programming: Loops and Control Flow

• While() Loop
• For() Loop
  
• Breaking out of or skipping Loops
  
• If()
  

Module 14: Writing your own functions

• Simple function and more advanced functions (Apply()/ Sapply()/ Mapply() etc)
• Regular Expression Text Extraction