What That Election Probability Means
We now have our presidential candidates, and for the next few months you get to hear about the changing probability of Hillary Clinton and Donald Trump winning the election. As of this writing, the Upshot estimates a 68% probability for Clinton and 32% for Donald Trump. FiveThirtyEight estimates 52% and 48% for Clinton and Trump, respectively. Forecasts are kind of all over the place this far out from November. Plus, the numbers aren’t especially accurate post-convention.
But the probabilities will start to converge and grow more significant.
So what does it mean when Clinton has a 68% chance of becoming president? What if there were a 90% chance that Trump wins?
Some interpret a high percentage as a landslide, which often isn’t the case with these election forecasts, and it certainly doesn’t mean the candidate with a low chance will lose. If this were the case, the Cleveland Cavaliers would not have beaten the Golden State Warriors, and I would not be sitting here hating basketball.
Fiddle with the probabilities in the graphic below to see what I mean.
Even when you shift the probability far left or far right, the opposing candidate still gets some wins. That doesn’t mean a forecast was wrong. That’s just randomness and uncertainty at play.
The probability estimates the percentage of times you get an outcome if you were to do something multiple times. In the case of Clinton’s 68% chance, run an election hundreds of times, and the statistical model that spit out the percentage thinks that Clinton wins about 68% of those theoretical elections. Conversely, it thinks Trump wins 32% of them.
So as we get closer to election day, even if there’s a high probability for one candidate over the other, what I’m saying is — there’s a chance.
- I’m writing this on July 27, 2016, so the probabilities on the Upshot and FiveThirtyEight are probably different by the time you’re reading this. Seriously, the numbers are all over the place right now.
- I used d3.js to make the chart using a clustered force layout. I used a similar method here and here.
Become a member. Support an independent site. Make great charts.See What You Get
Learn to Visualize Data See All →
How to Make Symbol-based Glyph Charts, with R Examples
Using geometric shapes as an encoding can provide another dimension to your charts.
How to Make a US County Thematic Map Using Free Tools
There are about a million ways to make a choropleth map. The problem is that a lot of solutions require expensive software or have a high learning curve. It doesn’t have to be that way.
How to Edit R Charts in Adobe Illustrator
A detailed guide for R users who want to polish their charts in the popular graphic design app for readability and aesthetics.
Jobs Charted by State and Salary →
Jobs and pay can vary a lot depending on where you live, based on 2013 data from the Bureau of Labor Statistics. Here’s an interactive to look.
Cycle of Many, a 24-hour snapshot for a day in the life of Americans
This is a 24-hour snapshot for a day in the life of Americans.
People get married at various ages, but there are definite trends that vary across demographic groups. What do these trends look like?