Dhrumil Mehta
Database Journalist, Politics @ FiveThirtyEight
Descisionmaking Beyond Prediction
Dhrumil Mehta
Associate Prof @ Columbia U. Graduate School of Journalism
Visiting Prof @ Harvard Kennedy School of Government
dhrumil.mehta@columbia.edu
@datadhrumil
@dmil
Guest Lecture @ Cornell Tech
"Off The Record" Please
Highlights:
Currently
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Associate Prof. @ Columbia Graduate School of Journalism
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Visiting Prof. @ Harvard Kennedy School
Previously
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Database Journalist, Politics @ FiveThirtyEight
- Software Development Engineer @ Amazon
- Northwestern:
- BA in Philosophy + Minor in Cognitive Science
- MS in Computer Science
Database Journalist, Politics
Themes
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Identifying editorial decisions when doing data analysis
- Communicating those decisions transparently and efficiently to readers
- Communicating uncertainty to readers
Data Collection
Datasets in the classroom
Datasets at work
Build our own dataset
- With Code / Scrapers
- By Hand
- By Survey Tool
Know your dataset
- Find the point at which the data was collected
- Can you see the actual forms or artifacts from the point of data collection?
- Read any documentation available about the data.
- People to consider contacting:
- Who collected the data?
- Who is the data collected from/about?
- Who are other users of this data?
- Who is impacted by this data?
- What are the limitations of this data collection?
- Be able to trace every statistical treatment that was applied from the raw form of the data to the current form and answer questions from your editors about the nature of the data
Collecting Polling Data
Bots
Internal Workflows
An Individual Poll
An Individual Poll
Editorial Descision making
Do you keep the poll in the polling average or do your remove it?
Aggregating Polls
Weighting polls by the historical accuracy of their pollster
But...How do we define historical accuracy?
- Polls from last 21 days prior to any election* since 1998
- What should we take into account?
Senate, House, Governor, Presidential and Pres Primary
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Step 1: Collect and classify polls
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Step 2: Calculate simple average error
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Step 3: Calculate Simple Plus-Minus
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Step 4: Calculate Advanced Plus-Minus
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Step 5: Calculate Predictive Plus-Minus
Step 3: Calculate Simple Plus-Minus
Step 4: Calculate Advanced Plus-Minus
Step 5: Calculate Predictive Plus-Minus
Accounts for other markers of quality like methodological standards (NCPP/AAPOR/Roper membership) and whether or not they call cell phones
But if the end goal is to know as much as we can about the state of an election, polls don't tell us everything...
Forecasting Elections
Communicating Probabilistic Data
Communicating Uncertainty
Communicating Uncertainty
Whether we show the chances in percentages or odds, this is the portion of an election forecast that is most anticipated — and has the most potential to be misunderstood. In 2016, we aimed for simplicity, both visually and conceptually. In 2018, we leaned into the complexity of the forecast. For 2020, we wanted to land somewhere in between.
Communicating Uncertainty
Communicating Uncertainty
https://fivethirtyeight.com/features/how-fivethirtyeights-2020-forecasts-did-and-what-well-be-thinking-about-for-2022/
Bots
Lets readers see results that FiveThirtyEight deems unexpected
Expectations are calibrated before results ever start coming in.
People, Data, and Systems
By Dhrumil Mehta
