PollTracker (PT) aggregates and averages all reputable public polls for a wide range of presidential, congressional, gubernatorial and state-level issue contests across the United States.
PollTracker uses the LOESS “regression analysis” library to generate its averages. The LOESS analysis is a statistical formula that integrates more current data with past polls in order to point a line in the direction the numbers are heading. PT “averages” are the endpoint of that line. The regression analysis was customized and developed in consultation with Professor Franklin. Its function is to derive trends from scatterings of polls, represented by the curved lines, taking into account both the different poll numbers and their progression over time.
Polltracker uses a process we call ‘segmenting’ to allow us to present data separated by large gaps of time on the same chart. Polltracker generates a ‘regression analysis’ – the smoothed, curvy lines on the graphs – for data sets with at least 10 data points and no gaps between data points of greater than 6 weeks. Gaps in the data of greater than six weeks are represented by a dotted line. Sets of continuous data with fewer than ten data points are calculated with a weighted mean average and represented by straight lines.