1. Course page is on line (Oct. 7)
  2. RHW1 Due is extended to Dec.3 at 12 noon. (For the extra point, the original due date (Nov.22) is valid.) (Nov.19)
  3. Midterm Result (Dec.3)
  4. R HW2 posted. (Dec.18)
  5. Quiz 1 & 2 Result (Dec.18)
  6. Quiz 3 Result (Dec.30)
  7. 6. Makeup Exam for Midterm:          Jan. 8 (Wed) at 11:30-12:50.
  8. Quiz 4 Result (Jan.8)
  9. RHW1 Result (Jan.10)
  10. RHW2 Result (Jan. 16)
  11. Final Exam Result (Feb.3)


This class is supported by DataCamp, the most intuitive learning platform for data science. Learn R, Python and SQL the way you learn best through a combination of short expert videos and hands-on-the-keyboard exercises. Take over 100+ courses by expert instructors on topics such as importing data, data visualization or machine learning and learn faster through immediate and personalised feedback on every exercise.


Link to the sign-up page

1st Assgnment Due on 22 Oct, 2019. Complete "Introduction to R" course.

2nd Assignment Due on 29 Oct, 2019. Complete "Intermediate to R" course.

3rd Assignment Due on 5 Nov. 2019. "Importing Data in R (part 1)" AND "Importing Data in R (part 2)".

4th Assignment Due on 12 Nov. 2019. "Cleaning Data in R" AND "Importing & Cleaning Data in R: Case Studies"

5th Assignment Due on 19 Nov. 2019. "Introduction to the Tidyverse" AND "Introduction to Function Writing in R"

6th Assignment Due on 3 Dec. 2019. "Data Visualization with ggplot2 (Part 1)" AND "Data Visualization with ggplot2 (Part 2)"

7th Assignment Due on 10 Dec. 2019. "Introduction to Data" AND "Data Manipulation in R with data.table"

8th Assignment Due on 17 Dec. 2019. "Joining Data in R with data.table" AND "Categorical Data in the Tidyverse"

9th Assignment Due on 24 Dec. 2019. "Communicating with Data in Tidyverse"



Lecture Notes

Week 1: Introduction

Week 2: Sampling 1

Week 3: Data types, Observational Study/Experiment, Describing Data Graphically1

Week 5: Describing Data Graphically 2, Describing Data Numerically

Week 6: Descriving Data Numerically 2

Week 7: Probability 1

Week 9: Probability 2, Random Variables

Week 10: Discrete Probability Distribution 1

Week 11: Discrete Probability Distribution 2

Week 12: Continuous Probability Distribution 1

Week 13: Continuous Probability Distribution 2 (Normal Distribution)  clip

Week 14: Continuous Probability Distribution 3 (Normal Approximation, Exponential Distribution)



Group RHW2 Instruction; Honor Code; Contribution Sheet

Group RHW1 Instruction; Honor Code; Contribution Sheet; gpa2019.csv; gpa2019.xlsx


Lecture Notes



Quiz Questions




R Learning Tool:  Sign up for the free R course at

and self-teach the basic operations of R. You will be more comfortable with R program.\

Podcast: DataFramed (post cast by Datacamp) to learn something about the world of data science and scientists.


Group Assignment


Practice Questions

Chapter 1: Questions, Answers

Chapter 2: Questions, Answers

Chapter 3: Questions, Answers

Chapter 4: Questions - part 1, part 2, Answers-part1, part2

Chapter 5: Questions - part1, part2, Answers - part1, part2

R Homework

R related

*Download R program from

step1: set CRAN (anywhere is fine, just pick one)

step2: select R according to your PC

You can also download a package named "Rcmdr"

step1: set CRAN if you haven't done so

step2: select "Rcmdr" from the list of packages

step3: once downloaded, click "load packages" from Packages tab, then you should see the Rcmdr window pops up.


After installing the latest R program, download R Studio.


References for R

Quick R

Introduction to R Programming Course at Edx (It's FREE!)

R ile Uygulamalı Analiz Yöntemleri – I       Murat Şirin (This one is also FREE!)