Course Schedule

  • Tuesday, September 23

    The singular of data is anecdote

    An introduction to public affairs reporting and the core skills of using data to find and tell important stories.
    Topics
    • Count something interesting
    • Make friends with math
    • The joy of text
    • How to do a data project
    Homework
    • Create a Github account and publish a document in Markdown
    • Critique a piece of data journalism
    • List your 10 favorite restaurants in a CSV file
    • List 10 news-related Twitter accounts that you find interesting
  • Thursday, September 25

    Bad big data

    Just because it's data doesn't make it right. But even when all the available data is flawed, we can get closer to the truth with mathematical reasoning and the ability to make comparisons, small and wide.
    Topics
    • Fighting bad data with bad data
    • Baltimore's declining rape statistics
    • FBI crime reporting
    • The Uber effect on drunk driving
    • Pivot tables
    Homework
    • Investigate Uber's purported impact on SF's DUI reports
    • Explore a snapshot of SF crime incident reports from 2014 with pivot tables
    • Read several essays on tracking homicides and shootings
    • Read The New Precision Journalism, Chapter 8: Databases
  • Tuesday, September 30

    DIY Databases

    Learn how to take data in your own hands. There are two kinds of databases: the kind someone else has made, and the kind you have to make yourself.
    Topics
    • The importance of spreadsheets
    • Counting murders
    • Making calls
    • A crowdsourced spreadsheet
    Homework
    • Create a data memo for your beat
    • Read Phillip Reese's stories and write a data critique on Phillip Reese's stories
    • Practice pivot tables with homicide data
  • Thursday, October 2

    Data in the newsroom

    Phillip Reese of the Sacramento Bee will discuss how he uses data in his investigative reporting projects.
    Topics
    • Phillip Reese speaks
    Homework
    • Create a Github Pages repository
    • Find 10 interesting online maps
    • Read these essays about maps
    • Look over my comments on your data beat memos
  • Tuesday, October 7

    The points of maps

    Mapping can be a dramatic way to connect data to where readers are and to what they recognize.
    Topics
    • Why maps work
    • Why maps don't work
    • Introduction to Fusion Tables and TileMill
    Homework
    • Map SFPD crimes
    • Map gun-related homicides
    • Sign up for the NICAR-L mailing list
    • Sign up for a StackOverflow account
    • Join the OpenData StackExchange community
  • Thursday, October 9

    The shapes of maps

    A continuation of learning mapping tools, with a focus on borders and shapes
    Topics
    • Working with KML files
    • Intensity maps
    • Visual joins and intersections
    Homework
    • A map of political change in the United States
    • Install Sequel Pro or SQLite Manager (optional)
  • Tuesday, October 14

    Introduction to SQL for Data Journalism

    The first in several sessions on learning SQL for the exploration of large datasets.
    Topics
    • MySQL / SQLite
    • Select, group, and aggregate
    • Where conditionals
    • SFPD reports of larceny, narcotics, and prostitution
    • Babies, and what we name them
    Homework
    • Read the SQL tutorials
    • Investigate your own name
  • Thursday, October 16

    A needle in multiple haystacks

    The ability to join different datasets is one of the most direct ways to find stories that have been overlooked.
    Topics
    • Inner joins
    • One-to-one relationships
    • Our politicians and what they tweet
    Homework
    • Map your name
  • Tuesday, October 21

    Haystacks without needles

    Sometimes, what's missing is more important than what's there. We will cover more complex join logic to find what's missing from related datasets.
    Topics
    • Left joins
    • NULL values
    • Which Congressmembers like Ellen Degeneres?
    Homework
    • Congress tweeting about Ebola
    • Read up on the LESO 1033 Program
  • Thursday, October 23

    Midterm Malarkey with Military Surplus

    A casual midterm covering the range of data analysis and programming skills acquired so far.
    Topics
    • A midterm on SQL and data
    • Data on military surplus distributed to U.S. counties
    • U.S. Census QuickFacts
    Homework
    • Do the Midterm
  • Tuesday, October 28

    Campaign Cash Check

    The American democratic process generates loads of interesting data and insights for us to examine, including who is financing political campaigns.
    Topics
    • Polling and pollsters
    • Following the campaign finance money
    • Competitive U.S. Senate races
    Homework
    • Analyze a Senate race's campaign spending
  • Thursday, October 30

    Predicting the elections

    With Election Day coming up, we examine the practices of polling as a way to understand various scenarios of statistical bias and error.
    Topics
    • Statistical significance
    • Poll reliability
    • Forecasting
    Homework
    • Analyze polling methodologies
    • Make your own poll-aggregating forecast
    • Senate prediction pool
    • Campaign finance data
  • Tuesday, November 4

    Election day (No class)

    Do your on-the-ground reporting
    Topics
    • No class because of Election Day Coverage
    Homework
  • Thursday, November 6

    Storytelling with Data Visualization

    While there are many tools and techniques for building data graphics, there is no magic visualization tool that will make a non-story worth telling.
    Topics
    • Review of the midterm
    • The importance of good data in visualizations
    • How visualization can augment the Serial podcast
    Homework
    • Proposal for data project
  • Tuesday, November 11

    Dirty data, cleaned dirt cheap

    One of the most tedious but important parts of data analysis is just cleaning and organizing the data. Being a good "data janitor" lets you spend more time on the more fun parts of journalism.
    Topics
    • Dirty data
    • OpenRefine
    • Clustering
    Homework
    • Clean up a dataset via data clustering
  • Thursday, November 13

    Guest speaker: Simon Rogers

    Simon Rogers, data editor at Twitter, talks about his work, how Twitter reflects how communities talk to each other, and the general role of data journalism.
    Topics
    • Ellen, World Cup, and other masses of Twitter data
    Homework
    • Status update on your project
  • Tuesday, November 18

    What we say and what we do

    When the data doesn't directly reveal something obvious, we must consider what its structure and its metadata implies.
    Topics
    • Proxy variables
    • Thanks Google for figuring out my commute
    • How racist are we, really?
    • How web sites measure us
    Homework
    • Status update No. 2 for your project
    • Read about visualizations, find a good visualization and a bad visualization
  • Thursday, November 20

    Project prep and discussion

    Discussion of final projects before the Thanksgiving break.
    Topics
    Homework
  • Tuesday, November 25

    Thanksgiving break

    Holiday - no class
    Topics
    Homework
  • Thursday, November 27

    Thanksgiving break

    Holiday - no class
    Topics
    Homework
  • Tuesday, December 2

    Project wrapup

    Last-minute help on final projects.
    Topics
    Homework
  • Thursday, December 4

    Project Show-N-Tell

    In-class presentations of our final data projects.
    Topics
    Homework