# The Comprehensive Statistics and Data Science with R Course

By: Geoffrey Hubona

- 19:42:10
- 219
- 25

- Language:
**English**

## Course Summary

This course, ** The Comprehensive Statistics and Data Science with R Course**, is mostly based on the authoritative documentation in the online "An Introduction to R" manual produced with each new R release by the Comprehensive R Archive Network

### Target Audience

- This course will benefit anyone wishing to learn R and especially those who seek an in-depth "hands-on" tutorial on performing statistical analyses with R.
- The course is useful for graduate students, college and university faculty, and working quantitative analysis professionals.

### Pre-Requisites

- Students must install R and RStudio (free software) but ample instructions are provided.

#### Curriculum

- Introduction 01:55
- Another Word about the Course and the Materials 04:50
- Introduction to Course Materials 08:43
- Session 1 Exercises 06:45
- Agenda and What is R ? (slides, Part 1) 08:35
- What is R ? (slides, part 2) 07:00
- What is R ? (slides, part 3) 06:54
- What is R ? (slides, part 4) 06:14
- What is R ? (slides, part 5) 06:45
- Reading in Data (part 1) 05:40
- Reading in Data (part 2) 06:27
- Reading in Data (part 3) 09:03

- Introduction to Section 2 05:53
- Vectors and Assignment (part 1) 05:37
- Vectors and Assignment (part 2) 04:24
- Vectors and Assignment (part 3) 05:37
- Vector Arithmetic (part 1) 05:26
- Vector Arithmetic (part 2) 04:41
- Vector Arithmetic (part 3) 05:49
- Vector Arithmetic (part 4) 04:02
- Vector Arithmetic (part 5) 05:58
- Generating Regular Sequences 04:35
- Logical Vectors 04:24
- More Missing Values; Character Vectors 04:28
- Index Vectors (part 1) 05:51
- Index Vectors (part 2) 06:57
- Index Vectors (part 3) 04:40
- Index Vectors (part 4) 02:05
- Session 2 Exercises 01:13

- Solutions to Session 2 Exercises (part 1) 05:33
- Solutions to Session 2 Exercises (part 2) 06:07
- Solutions to Session 2 Exercises (part 3) 04:23
- Objects and Classes 04:45
- Numeric Types 02:28
- Strings 02:24
- Factors 05:54
- Logical and Missing 05:08
- Vectors 03:41
- Vectorization and Recycling 05:06
- Basic Data Structures in R (slides, part 1) 04:55
- Basic Data Structures (slides, part 2) 05:28
- Basic Data Structures (slides, part 3) 05:55
- Objects: Script Examples (part 1) 05:22
- Objects: Script Examples (part 2) 06:02
- Objects: Script Examples (part 3) 05:54
- Objects: Script Examples (part 4) 05:17

- Session 4 Exercises 00:55
- More on Factors 05:39
- More on Factors and Strings (part 1) 05:13
- Factors and Strings (part 2) 05:03
- Factors and Strings (part 3) 04:58
- Function tapply() and Ragged Arrays 07:20
- Arrays 05:44
- Arrays and Matrices (part 1) 05:13
- Arrays and Matrices (part 2) 05:06
- Warpbreaks Data (part 1) 05:28
- Warpbreaks Data (part 2) 05:40
- More about Matrices (part 1) 05:14
- More about Matrices (part 2) 05:31
- More about Matrices (part 3) 06:22
- More about Matrices (part 4) 05:10
- More about Matrices (part 5) 04:36
- More about Matrices (part 6) 05:33
- Creating Matrices (part 1) 05:42
- Creating Matrices (part 2) 04:29
- Row Names and Column Names 05:36
- More on Array Function 05:14
- Outer Product of Two Arrays 05:48

- Introduction to Lists 05:56
- List Features and List Slicing (part 1) 06:05
- List Features and List Slicing (part 2) 05:33
- Accessing List Components (part 1) 05:51
- Accessing List Components (part 2) 05:42
- More List Dissection (part 1) 05:12
- More List Dissection (part 2) 04:07
- More About Lists 03:35
- What are Data Frames 05:17
- Characteristics of Data Frames 04:58
- A Data Frame is a List 04:48
- Data Frames are Lists 03:26
- Manipulating Data Frames (part 1) 04:52
- Manipulating Data Frames (part 2) 05:00
- Manipulating Data Frames (part 3) 05:10
- Manipulating Data Frames (part 4) 06:13
- Manipulating Data Frames (part 5) 04:19
- Manipulating Data Frames (part 6) 04:13
- Manipulating Data Frames (part 7) 04:27

- Exercise Solutions (part 1) 05:10
- Exercise Solutions (part 2) 05:20
- Exercise Solutions (part 3) 05:57
- Exercise Solutions (part 4) 04:58
- Exercise Solutions (part 5) 05:20
- Exercise Solutions (part 6) 06:00
- Exercise Solutions (part 7) 05:09
- Exercise Solutions (part 8) 05:38
- Introduction to Writing Functions in R 02:27
- Writing Functions (slides, part 1) 04:09
- Writing Functions (slides, part 2) 04:17
- Two Sample t-test (part 1) 04:54
- Two Sample t-test (part 2) 05:03
- Finish t-test Example; Named Arguments and Defaults 04:59
- Function Examples (part 1) 04:34
- "Many Means" Function Example 05:57
- Many Means and More 04:48
- More Functions Examples (part 1) 04:48
- More Functions Examples (part 2) 05:18
- Superassigment Examples (part 3) 04:57
- Superassignment Examples (part 4) 04:47
- Optional Arguments Example (part 5) 06:08
- parmax() and parmin() Functions Examples (part 6) 05:12
- parboth() Function Example (part 7) 04:45
- More Functions Examples (part 8) 04:31
- Still More Examples (part 9) 04:14
- Exercises for User Defined Functions Section 04:11

- User-Defined Functions Exercise 1a. Solution (part 1) 02:58
- User-Defined Functions Exercise 1a. Solution (part 2) 05:16
- User-Defined Functions Exercise 1b. Solution 06:25
- User-Defined Functions Exercise 2 Solution (part 1) 04:23
- User-Defined Functions Exercise 2 Solution (part 2) 04:48
- Introduction to R as a Statistical Environment 06:58
- Basic Operations (part 1) 03:52
- Basic Operations (part 2) 04:22
- Basic Operations (part 3) 04:45
- Presidential Height and Prussian Horsekicks (part 1) 05:04
- Presidential Height and Prussian Horsekicks (part 2) 04:44
- Prussian Horsekicks and Functions (part 1) 05:29
- Prussian Horsekicks and Functions (part 2) 05:19
- Functions; Vectors and Matrices (part 1) 05:58
- Functions; Vectors and Matrices (part 2) 05:37
- Functions; Vectors and Matrices (part 3) 05:48
- Data Frames and Histograms (part 1) 05:20
- Data Frames and Histograms (part 2) 05:57
- Attaching and Working with Data Frames (part 1) 04:34
- Attaching and Working with Data Frames (part 2) 04:17
- Attaching and Working with Data Frames (part 3) 05:12
- Entering Data Manually (part 1) 05:43
- Entering Data Manually (part 2) 05:15
- Entering Data Manually (part 3) 04:24
- Exercises for Working with R as a Statistical Environment 05:26
- Exercises Solutions (part 1) 03:49
- Exercises Solutions (part 2) 05:00
- Exercises Solutions (part 3) 04:42

- Statistical Modeling Operators in R (part 1) 05:33
- Statistical Modeling Operators in R (part 2) 05:51
- Statistical Modeling Operators in R (part 3) 05:04
- Analysis of Variance (ANOVA) (slides, part 1) 04:58
- ANOVA (slides, part 2) 05:22
- ANOVA (slides, part 3) 04:07
- ANOVA Scripts (part 1) 05:04
- ANOVA Scripts (part 2) 05:13
- ANOVA Scripts (part 3) 05:13
- ANOVA Scripts (part 4) 05:21
- ANOVA Scripts (part 5) 04:02
- ANOVA Scripts (part 6) 03:50
- What is Linear Modeling ? (slides, part 1) 05:12
- What is Linear Modeling ? (slides, part 2) 06:10
- What is Linear Modeling ? (slides, part 3) 02:57
- What is Linear Modeling ? (slides, part 4) 04:14
- Regression Domains (slides, part 1) 04:24
- Regression Domains (slides, part 2) 04:46
- Regression Script (part 1) 04:50
- Regression Scripts (part 2) 05:11
- Regression Scripts (part 3) 04:56
- Regression Scripts (part 4) 06:09
- Regression Scripts (part 5) 04:28
- Regression Scripts (part 6) 05:00
- Regression Scripts (part 7) 03:21
- Regression Scripts (part 8) 04:08
- Linear Modeling Exercise 01:49