Our first model is as simple as possible: We now compute the monthly mean of the $p_ Fixed sigma for the random walk Statistics are just hard and stubborn you know ?♂️ It's very probable that reaching out to peopleĬan have a selection effect on your sample, Note that we're talking about statistical bias here, not political bias: The model will be able to estimate this bias on the flyīut let's take a look at a crude estimation ourselves, to get a first idea. In line with the market average, some are below average, some are above. Instead we expect each pollster and each polling method to beĪt a different place on the spectrum: some report popularity rates We don't expect their results to be identical. To establish and question their samples each month, axvline ( date, color = "k", alpha = 0.6, linestyle = "-" ) legend () for date in newterm_dates : ax. values, "o", alpha = 0.3, label = "other" ) ax. values, "o", alpha = 0.3, label = "face to face" ) ax. index other = data != "face to face" ] dates_other = other. Than traditional models expect them to be.īy computing the monthly standard deviation of the approval ratesĮven though we probably should weigh themĪccording to their respective sample size):įace = data = "face to face" ] dates_face = face. Something that often proves challenging with count data Non-response rate is higher during Macron's term.While that's true, some events seem to push the approval rate back up,Ĭan that variance really be explained solely with a random walk?.Approval rates systematically decrease as the goes on.
We notice two things when looking at these plots: set_ylabel ( label ) for date in newterm_dates : ax. plot ( dates, rate, "o", alpha = 0.4 ) ax.
VIAVOICE SONDAGE ZIP
subplots ( 2, figsize = ( 12, 6 )) for ax, rate, label in zip ( axes. values doesnotrespond = 1 - approval_rates - disapproval_rates newterm_dates = data. Let's import those data, as well as the (fabulous) packages we'll need:Īpproval_rates = data. Of French presidents since the term limits switched to 5 years (in 2002). It's basically all the popularity opinion polls So we're not going to spend a lot of time explaining them.
It's always easier to start with 2 dimensions than 6, right?īut the model turned out to be so good at smoothingĪnd predicting popularity data that we thought it'd be a shame not to share it.
VIAVOICE SONDAGE TRIAL
This was supposed to be a trial run before working on an electoral modelįor the coming regional elections in France. Given that we only observe through the noisy data that are polls? To estimate the same process - what is the true latent popularity, To estimate the popularity of French presidents across time.Īnd helped me get familiar with the beauty of GPs.