ETC1010: Introduction to Data Analysis
Semester 1 2020
- Lecturer: Dr. Nicholas Tierney
- Chief Examiner: Di Cook
- Tutors: Steph Kobakian, Sherry Zhang, Sarah Belet, Nitika Kandhari
This is the course website. This page shows information about the consultation times, MoVE, and Schedule and lecture notes.
The “Assessments” tab above provides information about all assessment for ETC1010.
Expectations
- Unless your question is a personal issue or an administrative matter, please do not send us direct email. The ED site is appropriate for questions related to the course material.
- For personal or administrative issues, the email contact is: ETC1010.Clayton-x@monash.edu
- ED is used for asking for help, reading and lab exercise quizzes and assignment turn in. Only your name and email is stored in this system.
- If you register after the start of the semester or if you miss a lecture/lab, it is your responsibility to catch up with missed material, learn about due dates for material to be turned in, and getting assigned to a group for team work.
MoVE
Borrow a laptop: If you are enrolled in a MoVE unit and forget your laptop, or do not own one as yet, please visit Monash Connect to borrow a laptop for an activity or part of a day:
Clayton: 7.45AM - 5PM
You may be required to provide proof of ID (student card or personal ID) in order to borrow a laptop. We have a limited amount of laptops available for students to borrow (during semester only). Collect an IT Services ticket when you go to Monash Connect.
We will use the rstudio cloud server. In the future we may have R and Rstudio installed locally. When this happens, you can use USB stick, attach to the borrowed laptop, and install R, RStudio and all your packages on this. Use can then use the USB stick as your working environment, with the borrowed laptop simply as the computing engine.
Textbook
- R for Data Science
- Freely Available Online (https://r4ds.had.co.nz/)
- Also available for purchase on Amazon if you prefer a hardcopy.
- Readings for the semester are linked in the table below (some do not include the R4DS book)
Exercises on rstudio cloud (rstudio.cloud)
- You can follow the link on this slide to establish your account (this link will expire in week 3)
- Every time we go to use rstudio.cloud in class, you will log in to rstudio.cloud using your monash gmail account.
Consultation times
Consultations begin from Week 2 (16th March)
All consultations are in Menzies W1105
- Steph Kobakian: Tuesday 2-5pm
- Sarah Belet: Monday 3-4pm
- Sherry Zhang: Friday 1-2pm
- Nitika Kandhari: Tuesday 4-5pm
- Nick Tierney: Monday 12:00pm - 1pm
- Nick Tierney: Wednesday 10:30 - 11:30am
Practical Exam
Download the practical exam at this link (Opens at 12pm June 3rd)
Tentative Schedule
There are two lectorials posted online every week:
- Monday 4-6pm (online)
- Wednesday 12 - 2pm (online)
There are no lectorials during the midsemester break.
| Week | Lecture | Date | Slides | Topic | Exercise | Readings | Assessment |
|---|---|---|---|---|---|---|---|
| 1 | a | 2020-03-09 | Introduction to the language of data analysis | Chapter 4 (very short) | NA | ||
| 1 | b | 2020-03-11 | Chapters 1 - 4 in Rmarkdown for Scientists | NA | |||
| 2 | a | 2020-03-16 | Tidy data principles, reshaping your data into tidy form, and basic data wrangling | Chapter 12: Tidy Data | NA | ||
| 2 | b | 2020-03-18 | Chapter 5: Data Transformation | NA | |||
| Teaching Pause | |||||||
| 3 | a | 2020-03-30 | Plotting your data, and wrangling temporal data | Chapter 3: Data visualisation (again!) | NA | ||
| 3 | b | 2020-04-01 | Chapter 16: Dates and Times | NA | |||
| 4 | a | 2020-04-06 | Advanced wrangling, joining tables, and advanced data visualisation | Chapter 13: Relational Data | NA | ||
| 4 | b | 2020-04-08 | Chapter 1 of Data Visualisation: a Practical Introduction | Assignment 1 | |||
| Midsemester Break | |||||||
| 5 | a | 2020-04-20 | Handling missing values and scraping data |
Getting Started with Missing values Gallery of Missing Data Visualisations |
NA | ||
| 5 | b | 2020-04-22 | rvest description of selectorGadget | NA | |||
| 6 | a | 2020-04-27 | Introduction to modeling, and programming | Modelling Basics | NA | ||
| 6 | b | 2020-04-29 | Iteration | NA | |||
| 7 | a | 2020-05-04 | Intermediate models and programming | Many Models | NA | ||
| 7 | b | 2020-05-06 | none | NA | |||
| 8 | a | 2020-05-11 | Analysing text data |
Introduction to tidy text analysis Sentiment Analysis with tidy text |
NA | ||
| 8 | b | 2020-05-13 | n-grams | NA | |||
| 9 | a | 2020-05-18 | Wrangling, plotting and modeling network data | None | Assignment 2 | ||
| 9 | b | 2020-05-20 | None | NA | |||
| 10 | a | 2020-05-25 | Computational modeling, and good data collection practices | None | NA | ||
| 10 | b | 2020-05-27 | None | NA | |||
| 11 | a | 2020-06-01 | Guest Lecturer | None | Project Due | ||
| 11 | b | 2020-06-03 | Practical Exam | None | Practical Exam | ||
| 12 | a | 2020-06-08 | Project Presentation | None | Projects Presented | ||
| 12 | b | 2020-06-10 | Final Exam Review | None | Final Exam Review | ||