Good read/study on bias in big data/algorithms
Here’s a good read on Pew on AI and bias. It’s going to be an ongoing topic in your careers well beyond this class.
In-Class Exercise 4.2: Getting Familiar with Tableau
Here is the exercise.
And here is the spreadsheet you’ll need to complete the exercise [In-Class Exercise 4.2 – FoodAtlas.xlsx].
Make sure you right-click on the Excel file link and select “Save [Link] As…” to save it to your computer before starting the exercise.
Reading Quiz #3: Complete by February 13, 2017
Some quick instructions:
- You must complete the quiz by the start of class on February 13, 2017. The quiz is based on the readings for the whole week.
- When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. It will then take you to the quiz.
If it says you don’t have access, make sure you’re signed out of your regular Gmail (non-TUMail) account! - You can only do the quiz once. If you submit multiple times, I’ll only use the first (oldest) one.
- This is “open book” – you can use the articles to answer the questions – but do not get help from anyone else.
Ready? Take the quiz by clicking this link.
Readings for Week 4
Session 4.1:
- Chapter 2: Good Graphics? Handbook of Data Visualization (Unwin—-pages 57-77)
Session 4.2:
Weekly Question #3: Complete by February 13, 2017
Leave your response as a comment on this post by the beginning of class on February 16, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your opinions, not so much particular “facts” from the class!
If you sign in using your AccessNet ID and password you won’t have to fill in the name, email and captcha fields when you leave your comment.
In your opinion, what industries do you see as most affected by data science? Or better yet what industries do you see has most likely to be disrupted by big data/data science/analytics? How do you see data science affecting your career? Relate your observation to the class material if you can and what I outlined for media.
In-Class Exercise 4.1: Finding Good and Bad Visualizations
Here is the exercise
Here are the links in case you cannot click from the document.
Remember to leave a comment on this post with the link to your graphic for our discussion.
Assignment 2: Analyze a Data Set Using Tableau
Here is the assignment.
Here is the worksheet as a Word document to make it easy to fill in and submit (along with your Tableau file).
And here is the data file you will need to complete the assignment [In-Class Exercise 2.1 – 2015 Car Fuel Econ [Start].xlsx]. There is a deliverable sheet that needs to be emailed to me by Friday 2/17 at 3 p.m. Also Nathan will hold office hours on Thursday at 11:30 am – 1:00 pm (02/16) at Alter 236B.
Class Capture recordings here
There are recordings of what we went over in class so bookmark this link. The recording is on autopilot, but gives you a gist of what transpired.
Reading Quiz #2: Complete by Feb. 6, 2017
Some quick instructions:
- You must complete the quiz by the start of class on February 6, 2017. The quiz is based on the readings for the whole week.
- When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. It will then take you to the quiz.
If it says you don’t have access, make sure you’re signed out of your regular Gmail (non-TUMail) account! - You can only do the quiz once. If you submit multiple times, I’ll only use the first (oldest) one.
- This is “open book” – you can use the articles to answer the questions – but do not get help from anyone else.
Ready? Take the quiz by clicking this link.
Open Data Examples
In class we talked about a few examples of open data. Here are some others:
- Business: data.gov’s “Impact” section
- Science: The Genomes Unzipped project
- Government: New York City parking violations
- Journalism: Swarmize