With today’s combined two week Newspoll breakdown released over at the Oz, we can aggregate the results with the past two Nielsens and the JWS Godzilla poll to run some simulations. Ordinarily we make a pooled super sample of all the polls,  weighted by sample size, to get aggregate state results from which to crunch the numbers. Yet, with the JWS monster and it’s 28,000 sample, it poses a problem since it would simply dominate the simulation results (not that it would actually matter — but more on that later) because its sample is so large. To get around this issue, we’ll pull the weight of the JWS poll down to 40% — letting the Newspoll and Nielsen take the remaining 60% of the pooled sample weight.

Here, we’re running our quasi-dependency Monte Carlo simulation method that treats individual seat results as neither dependent nor independent events, imitating the real world effect we see (or, at least,  we think we see) happen at elections, where seats “move together” at the state level of aggregation (not that it actually makes much difference at the moment!)

So crunching these numbers — taking about 30,000 simulated elections — this is what the probability distribution of the change in seats from the current Parliament looks like:

simhistaug18

While the more useful cumulative probability distribution comes in like this:

simcumulativeaug18

To read the chart, choose a number at the bottom of the chart — the left-hand axis tells you the implied probability of the ALP winning at least that many seats were an election held over the past fortnight and the election result was consistent with the polling results.