Who’s Leading Whom? Predictive Markets Versus Polls

We recently had the opportunity to post a guest entry at one of our favorite data visualization blogs – Flowing Data. In it, we examined to what extent election polls and election betting data are correlated and whether one leads or lags the other. Check out the full post at Flowing Data. Below we have provided our packaged workbook and data for your own exploration.
We recently had the opportunity to post a guest entry at one of our favorite data visualization blogs – Flowing Data. In it, we examined to what extent election polls and election betting data are correlated and whether one leads or lags the other. Check out the full post at Flowing Data. Below we have provided our packaged workbook and data for your own exploration.

The attached packaged workbook offers quick filters that let you interactively explore the leading/lagging correlation in more detail. You can view this packaged workbook using the free Tableau Reader, or for a complete experience download the free trial of Tableau Desktop.

This workbook helped us explore how to generate a smoothed version of the raw polling and Intrade data, as visualized in the middle pane of our guest post chart. This was a key step in our analysis, because the final pane uses a rate-of-change table calculation in Tableau that is very sensitive to the rapid day-to-day changes in both the polling data and the Intrade data. Like focusing a camera lens, we needed to blur the short-duration changes in order to focus our attention on the longer-term trends.

Using Tableau's quick filters in the attached workbook, you can experiment with the parameters for our approximate-Gaussian smoothing filter. You can see how important it is to use a good low-pass filter; for example, a Gaussian must be “clipped” in practice (to yield a finite support), but too much clipping erodes its low-pass characteristics and produces graphs which are significantly obscured by high-frequency noise.