Introduction
  • You, This course and Us
  • Top Down vs Bottoms Up : The Google vs McKinsey way of looking at data
  • R and RStudio installed
The 10 second answer : Descriptive Statistics
  • Descriptive Statistics : Mean, Median, Mode
  • Our first foray into R : Frequency Distributions
  • Draw your first plot : A Histogram
  • Computing Mean, Median, Mode in R
  • What is IQR (Inter-quartile Range)?
  • Box and Whisker Plots
  • The Standard Deviation
  • Computing IQR and Standard Deviation in R
Inferential Statistics
  • Drawing inferences from data
  • Random Variables are ubiquitous
  • The Normal Probability Distribution
  • Sampling is like fishing
  • Sample Statistics and Sampling Distributions
Case studies in Inferential Statistics
  • Case Study 1 : Football Players (Estimating Population Mean from a Sample)
  • Case Study 2 : Election Polling (Estimating Population Proportion from a Sample)
  • Case Study 3 : A Medical Study (Hypothesis Test for the Population Mean)
  • Case Study 4 : Employee Behavior (Hypothesis Test for the Population Proportion)
  • Case Study 5: A/B Testing (Comparing the means of two populations)
  • Case Study 6: Customer Analysis (Comparing the proportions of 2 populations)
Diving into R
  • Harnessing the power of R
  • Assigning Variables
  • Printing an output
  • Numbers are of type numeric
  • Characters and Dates
  • Logicals
Vectors
  • Data Structures are the building blocks of R
  • Creating a Vector
  • The Mode of a Vector
  • Vectors are Atomic
  • Doing something with each element of a Vector
  • Aggregating Vectors
  • Operations between vectors of the same length
  • Operations between vectors of different length
  • Generating Sequences
  • Using conditions with Vectors
  • Find the lengths of multiple strings using Vectors
  • Generate a complex sequence (using recycling)
  • Vector Indexing (using numbers)
  • Vector Indexing (using conditions)
  • Vector Indexing (using names)
Arrays
  • Creating an Array
  • Indexing an Array
  • Operations between 2 Arrays
  • Operations between an Array and a Vector
  • Outer Products
Matrices
  • A Matrix is a 2-Dimensional Array
  • Creating a Matrix
  • Matrix Multiplication
  • Merging Matrices
  • Solving a set of linear equations
Factors
  • What is a factor?
  • Find the distinct values in a dataset (using factors)
  • Replace the levels of a factor
  • Aggregate factors with table()
  • Aggregate factors with tapply()
Lists and Data Frames
  • Introducing Lists
  • Introducing Data Frames
  • Reading Data from files
  • Indexing a Data Frame
  • Aggregating and Sorting a Data Frame
  • Merging Data Frames
Regression quantifies relationships between variables
  • Introducing Regression
  • What is Linear Regression?
  • A Regression Case Study : The Capital Asset Pricing Model (CAPM)
Linear Regression in Excel
  • Linear Regression in Excel : Preparing the data
  • Linear Regression in Excel : Using LINEST()
Linear Regression in R
  • Linear Regression in R : Preparing the data
  • Linear Regression in R : lm() and summary()
  • Multiple Linear Regression
  • Adding Categorical Variables to a linear model
  • Robust Regression in R : rlm()
  • Parsing Regression Diagnostic Plots
Data Visualization in R
  • Data Visualization
  • The plot() function in R
  • Control color palettes with RColorbrewer
  • Drawing barplots
  • Drawing a heatmap
  • Drawing a Scatterplot Matrix
  • Plot a line chart with ggplot2