Dr Kasım Zor

EEE356 - Data Analytics [R] (2023-2024 Spring)

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Main Course

• Venue: D204, M2 Building

• Date&Time: 09:45-12:00 on Mondays

• Objectives: This course aims to gain students insight and required skills related to data analytics containing R Programming, data wrangling, data visualisation, exploratory data analysis, and approaches to missing data.

• Textbook:

  • Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund, R for Data Science, 2nd Ed., O'Reilly​, 2023. (English, Turkish)

• Contents: Introduction to Data Analytics, Introduction to R Programming Language, Data Structures, Control Structures, Functions, Introduction to Data Visualisation, Data Transformation, Data Wrangling, Data Visualisation (ggplot2, Layers, Scales, and The Grammar), Exploratory Data Analysis, and Approaches to Missing Data.

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Laboratory

• Venue: Computer Lab, M1 Building

• Date&Time: 12:30-15:15 on Wednesdays (Two Groups)

  • Group 1 - 12:30-13:45​

  • Group 2 - 14:00-15:15

• Platform: DataCamp Classrooms

 

Exams

• Week 9 - Midterm Examination: (2024) (2021)

• Week 16 - Final Examination: (2021)

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Lecture Documents

1. Course Introduction and Scope

2. Introduction to Data Analytics

3. Hands-on Exercise: RStudio

4. Hands-on Exercise: Tidyverse

5. Introduction to

   1. Quarto Markdown

   2. Data Visualisation (The Joy of Stats)

6. Data Transformation

7. Data

   1. Tidying​

   2. Import

8. Advanced Data Visualisation

   1. Layers​

   2. Exploratory Data Analysis

   3. Communication

9. Advanced Data Transformation

   1. Logical Vectors​

   2. Numbers

   3. Strings

   4. Regular Expressions

10. Advanced Data Transformation

    1. Factors​

    2. Date and Times

    3. Missing Values

    4. Joins

11. Advanced Data Import

    1. Spreadsheets​

    2. Databases

    3. Arrow

    4. Hierarchical Data

    5. Web Scraping

12. Hands-on Exercise: Correlation Map with ggstatsplot

13. Hands-on Exercise: Single Imputation with imputeTS

14. Homework: Shiny (Recommended Book)

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Laboratory Documents​

• ​RStudio Installation

• Introduction to RStudio (Reference: Prof. Trevor Hastie, Statistical Learning)

• Joining EEE356 Team in DataCamp Classrooms

• ​DataCamp Classrooms: Introduction to R​​​​

• DataCamp Classrooms: Introduction to the Tidyverse​​

• DataCamp Classrooms: Introduction to Data Visualisation with ggplot2

• DataCamp Classrooms: Exploratory Data Analysis with R

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Announcements

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