SUMMARY OF EVERYT HING
LECTURES, CODE EXAMPLES, TIPS & STEP -BY-STEP ASSIGNMENT 1 GUIDE .
Note: This course has no readings.
Enhanced with a dynamic table of contents.
, MADS MADLAD |2
Note from MADS MADLAD:
Thank you for buying my summary. When I was writing these I sometimes
struggled with this program, but there were no summaries available. This is
why I decided to write something that is truly complete with a lot of effort put
into it.
It helped me and my friends get good grades, but I always had you in mind, the
future reader. When necessary, I always went the extra mile to make my
summaries, more readable, organized and complete.
If you feel like it, leave me a review of how the course is going using this
summary, it will make my day to hear your feedback.
Check out my other extensive summaries for other MADS courses:
Contact info:
If you need help or have an inquiry, contact me: https://www.georgedreemer.com
Connect with me on LinkedIn: https://www.linkedin.com/in/georgedreemer/
Donations:
By no means am I looking for fellow students to send me money! But if you feel like sending
me some ETH or BTC, you can do so here:
--> ETH: 0x123e086c6808459e7fC6Ac7F64a77dBA1dDe0149
--> BTC: bc1qgwzc82vph5v8rmzef4ywechjf85772n7m2e22g
, MADS MADLAD |3
wishes you g ood luck & persev erance.
Grades Testimony:
, MADS MADLAD |4
Table of Contents
Week 1 (Lecture 1)........................................................................................... 10
Lecture 1 – Intro to R + Intermediate R ......................................................... 10
Introduction to R: Variables, Vectors, Matrices, Factors, Data Frames and
Lists............................................................................................................ 10
Variables .............................................................................................. 10
Vectors ................................................................................................. 10
Matrices ............................................................................................... 10
Factors ................................................................................................. 11
Data Frames (DF).................................................................................. 11
Lists ...................................................................................................... 12
Intermediate R: Conditionals, Control flow, Loops, Functions, Apply family,
Utilities. ..................................................................................................... 12
Conditionals and Control Flow ............................................................. 12
- Relational operators ................................................................... 12
- Logical operators ........................................................................ 13
- Conditional Statements .............................................................. 13
Loops.................................................................................................... 14
- While loops ................................................................................ 14
- For loops .................................................................................... 14
Functions.............................................................................................. 15
Apply family ......................................................................................... 16
- Lapply ......................................................................................... 16
- Sapply ......................................................................................... 16
- Vapply ........................................................................................ 17
Utilities ................................................................................................. 17
- Data utilities ............................................................................... 18
- Importing Data in R .................................................................... 19
Week 2 (Lecture 2)........................................................................................... 20
Lecture 2 – Reducing data complexity .......................................................... 20
LECTURES, CODE EXAMPLES, TIPS & STEP -BY-STEP ASSIGNMENT 1 GUIDE .
Note: This course has no readings.
Enhanced with a dynamic table of contents.
, MADS MADLAD |2
Note from MADS MADLAD:
Thank you for buying my summary. When I was writing these I sometimes
struggled with this program, but there were no summaries available. This is
why I decided to write something that is truly complete with a lot of effort put
into it.
It helped me and my friends get good grades, but I always had you in mind, the
future reader. When necessary, I always went the extra mile to make my
summaries, more readable, organized and complete.
If you feel like it, leave me a review of how the course is going using this
summary, it will make my day to hear your feedback.
Check out my other extensive summaries for other MADS courses:
Contact info:
If you need help or have an inquiry, contact me: https://www.georgedreemer.com
Connect with me on LinkedIn: https://www.linkedin.com/in/georgedreemer/
Donations:
By no means am I looking for fellow students to send me money! But if you feel like sending
me some ETH or BTC, you can do so here:
--> ETH: 0x123e086c6808459e7fC6Ac7F64a77dBA1dDe0149
--> BTC: bc1qgwzc82vph5v8rmzef4ywechjf85772n7m2e22g
, MADS MADLAD |3
wishes you g ood luck & persev erance.
Grades Testimony:
, MADS MADLAD |4
Table of Contents
Week 1 (Lecture 1)........................................................................................... 10
Lecture 1 – Intro to R + Intermediate R ......................................................... 10
Introduction to R: Variables, Vectors, Matrices, Factors, Data Frames and
Lists............................................................................................................ 10
Variables .............................................................................................. 10
Vectors ................................................................................................. 10
Matrices ............................................................................................... 10
Factors ................................................................................................. 11
Data Frames (DF).................................................................................. 11
Lists ...................................................................................................... 12
Intermediate R: Conditionals, Control flow, Loops, Functions, Apply family,
Utilities. ..................................................................................................... 12
Conditionals and Control Flow ............................................................. 12
- Relational operators ................................................................... 12
- Logical operators ........................................................................ 13
- Conditional Statements .............................................................. 13
Loops.................................................................................................... 14
- While loops ................................................................................ 14
- For loops .................................................................................... 14
Functions.............................................................................................. 15
Apply family ......................................................................................... 16
- Lapply ......................................................................................... 16
- Sapply ......................................................................................... 16
- Vapply ........................................................................................ 17
Utilities ................................................................................................. 17
- Data utilities ............................................................................... 18
- Importing Data in R .................................................................... 19
Week 2 (Lecture 2)........................................................................................... 20
Lecture 2 – Reducing data complexity .......................................................... 20
