TruthIsAll
10-06-2008, 05:44 AM
Oct.6
The usual DU naysayers question the Election ModelEV Simulation
http://www.democraticunderground.com/discuss/duboard.php?az=view_all&address=203x508722#508961
This is the fivethirtyeight.com electoral vote frequency graph:
http://4.bp.blogspot.com/_ov-pT1x-W8Y/SNU03EJMSzI/AAAAAAAACYE/IQVTZ_z7L9I/S1600-R/0920_evdist.png
This is the electoral vote frequency distribution produced by the Election Model Monte Carlo simulation:
http://www.RichardCharnin.com/2008ElectionModel_30550_image001.gif
Has Febble ever developed a model which uses the Monte Carlo Simulation method?
Does Febble know how to calculate the EXPECTED electoral vote based on the latest state polls?
Can she describe how the Election Model derives the electoral vote distribution histogram step-by-step?
Can she describe how 538.com derives the electoral vote distribution histogram step-by-step?
Can she describe the algorithm she would use to calculate the EV distribution – step-by-step?
Does she realize that Princeton Professor Sam Wang derives virtually identical results as the Election Model using his exhaustive combinatorial meta-analysis model?
Is Febble aware of the fact that 538.com uses factors other than state polls in projecting the EV and win probability?
Is she aware that 538.com projects Election Day results while the Election Model assumes a FRAUD-FREE election is held TODAY?
These are the first 20 of 5000 election trials using polling data as of Oct.6.
http://www.RichardCharnin.com/MonteCarloEVSimulation20trials1006.pdf
Obama won all 5000 election trials. How would Febble calculate his EV win probability? Febble should calculate the average EV of the 20 trials and see how close it is to the expected 358 EV.
OnTheOtherHand talks about pixels and ogives while totally avoiding the mathematics. Look at the 538 curve. About 13% of the election trials are below 270. Graph pixels have nothing do with the basic simulation results.
THIS IS WHAT IS RELEVANT: Look at the Oct. 6 graph. ALL 5000 election trials result in Obama winning more than 270 EV. The histogram breaks up the distribution into increments of 5 EV which is a reasonable bin size. Would OTOH suggest a bin size of ONE?
In fact, Excel has a limit of approximately 40 bins in its Histogram program. Does OTOH know what a frequency distribution curve is? Does he know what the cumulative distribution curve represents?
The basic statistics which define the frequency histogram are what counts:
The MEAN, MEDIAN, MAXIMUM, MINIMUM, 95% CONFIDENCE INTERVAL.
Note that the mean and median are virtually identical, a clear indication of the LAW OF LARGE NUMBERS. It proves that 5000 simulations are SUFFICIENT TO ILLUSTRATE THE CONVERGENCE TO THE THEORETICAL MEAN (EXPECTED ELECTORAL VALUE).
The expected EV (mean) is calculated as a simple summation:
Expected EV = ∑ P(i) * EV (i), for i=1, 51 states.
P(i) is the probability of winning state (i) and its EV(i) electoral votes.
P(i) is calculated using the most recent state poll average vote share adjusted for an undecided voter allocation normal distribution. A 4% state poll margin of error is assumed.
OTOH may be interested in this graph of 5000 election trials, which is not a histogram but shows that Obama won all 5000 trials:
http://www.geocities.com/electionmodel/2008ElectionModel_3523_image001.gif
The usual DU naysayers question the Election ModelEV Simulation
http://www.democraticunderground.com/discuss/duboard.php?az=view_all&address=203x508722#508961
This is the fivethirtyeight.com electoral vote frequency graph:
http://4.bp.blogspot.com/_ov-pT1x-W8Y/SNU03EJMSzI/AAAAAAAACYE/IQVTZ_z7L9I/S1600-R/0920_evdist.png
This is the electoral vote frequency distribution produced by the Election Model Monte Carlo simulation:
http://www.RichardCharnin.com/2008ElectionModel_30550_image001.gif
Has Febble ever developed a model which uses the Monte Carlo Simulation method?
Does Febble know how to calculate the EXPECTED electoral vote based on the latest state polls?
Can she describe how the Election Model derives the electoral vote distribution histogram step-by-step?
Can she describe how 538.com derives the electoral vote distribution histogram step-by-step?
Can she describe the algorithm she would use to calculate the EV distribution – step-by-step?
Does she realize that Princeton Professor Sam Wang derives virtually identical results as the Election Model using his exhaustive combinatorial meta-analysis model?
Is Febble aware of the fact that 538.com uses factors other than state polls in projecting the EV and win probability?
Is she aware that 538.com projects Election Day results while the Election Model assumes a FRAUD-FREE election is held TODAY?
These are the first 20 of 5000 election trials using polling data as of Oct.6.
http://www.RichardCharnin.com/MonteCarloEVSimulation20trials1006.pdf
Obama won all 5000 election trials. How would Febble calculate his EV win probability? Febble should calculate the average EV of the 20 trials and see how close it is to the expected 358 EV.
OnTheOtherHand talks about pixels and ogives while totally avoiding the mathematics. Look at the 538 curve. About 13% of the election trials are below 270. Graph pixels have nothing do with the basic simulation results.
THIS IS WHAT IS RELEVANT: Look at the Oct. 6 graph. ALL 5000 election trials result in Obama winning more than 270 EV. The histogram breaks up the distribution into increments of 5 EV which is a reasonable bin size. Would OTOH suggest a bin size of ONE?
In fact, Excel has a limit of approximately 40 bins in its Histogram program. Does OTOH know what a frequency distribution curve is? Does he know what the cumulative distribution curve represents?
The basic statistics which define the frequency histogram are what counts:
The MEAN, MEDIAN, MAXIMUM, MINIMUM, 95% CONFIDENCE INTERVAL.
Note that the mean and median are virtually identical, a clear indication of the LAW OF LARGE NUMBERS. It proves that 5000 simulations are SUFFICIENT TO ILLUSTRATE THE CONVERGENCE TO THE THEORETICAL MEAN (EXPECTED ELECTORAL VALUE).
The expected EV (mean) is calculated as a simple summation:
Expected EV = ∑ P(i) * EV (i), for i=1, 51 states.
P(i) is the probability of winning state (i) and its EV(i) electoral votes.
P(i) is calculated using the most recent state poll average vote share adjusted for an undecided voter allocation normal distribution. A 4% state poll margin of error is assumed.
OTOH may be interested in this graph of 5000 election trials, which is not a histogram but shows that Obama won all 5000 trials:
http://www.geocities.com/electionmodel/2008ElectionModel_3523_image001.gif