# Learn By Example: Statistics and Data Science in R

By: Loonycorn A 4-Ppl Team;ex-Google.

- 08:56:25
- 96
- 236

- Language:
**English**

## Course Summary

**Taught by** a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce.

**This R Programming tutorial is a gentle yet thorough introduct**

### Target Audience

- Yep! MBA graduates or business professionals who are looking to move to a heavily quantitative role
- Yep! Engineers who want to understand basic statistics and lay a foundation for a career in Data Science
- Yep! Analytics professionals who have mostly worked in Descriptive analytics and want to make the shift to being modelers or data scientists
- Yep! Folks who've worked mostly with tools like Excel and want to learn how to use R for statistical analysis

### Pre-Requisites

No prerequisites : We start from basics and cover everything you need to know. We will be installing R and RStudio as part of the course and using it for most of the examples. Excel is used for one of the examples and basic knowledge of excel is assumed.

#### Curriculum

- Download for sec 1
- You, This course and Us
- Top Down vs Bottoms Up : The Google vs McKinsey way of looking at data 13:11
- R and RStudio installed 05:10

- Download for sec 2
- Descriptive Statistics : Mean, Median, Mode 10:07
- Our first foray into R : Frequency Distributions 06:06
- Draw your first plot : A Histogram 03:11
- Computing Mean, Median, Mode in R 02:21
- What is IQR (Inter-quartile Range)? 08:08
- Box and Whisker Plots 03:11
- The Standard Deviation 10:24
- Computing IQR and Standard Deviation in R 06:06

- Downloads for Sec 3
- Drawing inferences from data 03:25
- Random Variables are ubiquitous 16:54
- The Normal Probability Distribution 09:31
- Sampling is like fishing 06:14
- Sample Statistics and Sampling Distributions 09:25

- Downloads for Sec 4
- Case Study 1 : Football Players (Estimating Population Mean from a Sample) 06:45
- Case Study 2 : Election Polling (Estimating Population Proportion from a Sample) 07:50
- Case Study 3 : A Medical Study (Hypothesis Test for the Population Mean) 13:53
- Case Study 4 : Employee Behavior (Hypothesis Test for the Population Proportion) 09:49
- Case Study 5: A/B Testing (Comparing the means of two populations) 17:18
- Case Study 6: Customer Analysis (Comparing the proportions of 2 populations) 11:50

- Downloads for Sec 5
- Harnessing the power of R 07:26
- Assigning Variables 08:47
- Printing an output 13:03
- Numbers are of type numeric 05:24
- Characters and Dates 07:30
- Logicals 03:24

- Downloads for Sec 6
- Data Structures are the building blocks of R 08:24
- Creating a Vector 02:22
- The Mode of a Vector 04:18
- Vectors are Atomic 02:24
- Doing something with each element of a Vector 03:09
- Aggregating Vectors 01:28
- Operations between vectors of the same length 05:39
- Operations between vectors of different length 05:30
- Generating Sequences 06:25
- Using conditions with Vectors 02:04
- Find the lengths of multiple strings using Vectors 02:22
- Generate a complex sequence (using recycling) 02:49
- Vector Indexing (using numbers) 06:56
- Vector Indexing (using conditions) 06:18
- Vector Indexing (using names) 02:27

- Downloads for Sec 7
- Creating an Array 11:36
- Indexing an Array 07:38
- Operations between 2 Arrays 02:45
- Operations between an Array and a Vector 02:09
- Outer Products 06:23

- Downloads for Sec 8
- A Matrix is a 2-Dimensional Array 07:58
- Creating a Matrix 02:00
- Matrix Multiplication 02:48
- Merging Matrices 02:06
- Solving a set of linear equations 02:06