Syllabus, COMM 273D (Fall 2014)

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When: Tuesdays and Thursdays, 2:15 to 3:45 PM

Where: McClatchy 410

Who: Dan Nguyen

  • email: dun at stanford dot-ee-dee-euu
  • twitter: @dancow
  • office: McClatchy 342

Description

Even before the ubiquity of Internet access and high-powered computers, public accountability reporting relied on the concerted collection of observations and analytical problem-solving. We study the methods, and the data, used to discover leads and conduct in-depth reporting on public affairs, including election finance and safety regulations. Students gain practical experience with the digital tools and techniques of computer-assisted reporting. Prerequisite: Journalism M.A. student.*

Tools and technology

The work and exercises in this class should be doable with any Windows, Mac, or Linux computer capable of running a modern web browser.

  • Text editor: I recommend Sublime Text. In the lab, we'll be using TextWrangler.
  • Spreadsheet: In-class demonstrations will involve Google Spreadsheets. Microsoft Excel will also do fine.
  • Database: In-class demonstrations will use Sequel Pro, which is available only for Mac. On your own laptop, I recommend (for ease of installation) installing the Firefox web browser and using the SQLite Manager.

Technical frustrations

This class is not meant to be torture. This class is not about programming but you will actually be doing programming when doing things such as SQL database queries. This is a s

Grading

The course grade is based off of homework (40%), attendance (10%), and a final project (50%). For the final project, students will be expected to

Academic Honesty

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About Stanford

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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.
    • Count something interesting
    • Make friends with math
    • The joy of text
    • How to do a data project
  • 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.
    • Fighting bad data with bad data
    • Baltimore's declining rape statistics
    • FBI crime reporting
    • The Uber effect on drunk driving
    • Pivot tables
  • 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.
    • The importance of spreadsheets
    • Count something interesting
    • Counting murders
    • Making calls
    • A crowdsourced spreadsheet
    • Building interactives from spreadsheets
  • Thursday, October 2

    Data in the newsroom

    Phillip Reese of the Sacramento Bee will discuss how he uses data in his investigative reporting projects.
    • Phillip Reese speaks
  • Tuesday, October 7

    Maps and lists

    Mapping can be a dramatic way to relate data to where people are and what they recognize. Lists are as powerful as they are simple to make.
    • The precision of a list
    • The personal touch of a map
  • Thursday, October 9

    The forms of death

    Data is often constrained, and sometimes distorted, by the tools and questions used to collect it.
    • Filling in the blanks of data acquisition
  • Tuesday, October 14

    Say my name

    The first in several sessions on learning SQL for the exploration of large datasets.
    • Select, group, and aggregate
    • Index when necessary
    • Where conditionals
    • The SSA's popular baby names list
    • Re-examining SF crime
  • 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.
    • Inner joins
  • Tuesday, October 21

    Haystacks without needles

    Sometimes, what's missing is more important than what's there. We will cover more complex join logic, including the ability to find what's absent in one dataset compared to the other.
  • Thursday, October 23

    Data janitorial work

    Life is messy, and so is its data. Knowing how to resourcefully clean and manage data is critical to exploring data.
  • Tuesday, October 28

    Datapalooza

    Putting all the data together without being overwhelming.
  • Thursday, October 30

    Election data

    The American democratic process generates loads of interesting data and insights for us to examine.
  • Tuesday, November 4

    Election day analysis

    Political data analysis continued.
  • Thursday, November 6

    Killer visualizations

    We have an abundance of data, but a scarcity of attention. Visualizations can more clearly communicate a story than do words, but are just as susceptible in misleading or confusing the viewer.
  • Tuesday, November 11

    How to die with statistics

    With big numbers often come too big of assumptions. Don't let your stories be undermined by poor interpretations and calculations of the data.
  • Thursday, November 13

    Data exploration and joining

    We'll walk through a real-world data exercise, including data cleaning, joining, and queries.
  • 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.
  • Thursday, November 20

    Project prep and discussion

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

    Thanksgiving break

    Holiday - no class
  • Thursday, November 27

    Thanksgiving break

    Holiday - no class
  • Tuesday, December 2

    Project wrapup

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

    Project Show-N-Tell

    In-class presentations of our final data projects.