Main Ideas

Coming Due Soon

Guidelines for Discussion

Data Representation

Misleading Data Visualizations1

What Baby Boomers Think

  • What is the graph trying to show?

  • Why is this graph misleading?

  • How can you improve this graph?

Brexit

Brexit

  • What is the graph trying to show?

  • Why is this graph misleading?

  • How can you improve this graph?

Spurious Correlations2

A Spurious Correlation

  • What is the graph trying to show?

  • Why is this graph misleading?

Collecting + handling data3

Web scraping

A researcher is interested in the relationship of weather to sentiment (positivity or negativity of posts) on Twitter. They want to scrape data from https://www.wunderground.com and join that to Tweets in that geographic area at a particular time. One complication is that Weather Underground limits the number of data points that can be downloaded for free using their API (application program interface). The researcher sets up six free accounts to allow them to collect the data they want in a shorter time-frame.

A data analyst received permission to post a data set that was scraped from a social media site. The full data set included name, screen name, email address, geographic location, IP (Internet protocol) address, demographic profiles, and preferences for relationships. The analyst removes name and email address from the data set in effort to deidentify it.

Algorithmic bias: deep dive

- Video

- Slides

Discussion questions

  • Ezinne mentions a phenomenon called “Simpson’s Paradox”, where conclusions drawn from analyzing subgroups differ from conclusions drawn when the groups are combined. Where else have you seen Simpson’s Paradox in this class?

  • A company uses a machine learning algorithm to determine which job advertisement to display for users searching for technology jobs. Based on past results, the algorithm tends to display lower paying jobs for women than for men (after controlling for other characteristics than gender). What ethical considerations might be considered when reviewing this algorithm?4

  • As you start working on data analyses for the STA 199 project, internships, research, etc., what are 1 - 2 things you can do to ensure you’re doing the analysis in an ethical way?


  1. Source: https://humansofdata.atlan.com/2019/02/dos-donts-data-visualization↩︎

  2. Source: https://www.tylervigen.com/spurious-correlations Content warning: some examples include death or suicide.↩︎

  3. Modified from Modern Data Science with R, 2nd Edition↩︎

  4. Source: Modern Data Science with R, 2nd Edition↩︎