The odds that 600 of 1000 random machine errors favor Bush:1 in 11 BILLION

[TruthIsAll]

The odds are 1 in 11 BILLION that 600 of 1000 random machine errors would favor Bush.

Once again, in Excel:
Probability = 1-BINOMDIST(600,1000,0.5,TRUE)
= 0.0000000000900598
or 1 out of 11,103,727,321

Here are the odds that N out of 1000 random machine gliches would favor Bush due to chance:

N...Odds
500 2 <<< this is what we would normally expect to occur
510 4
520 10
530 37
540 193
550 1,437
560 15,654
570 250,812
580 5,949,049
590 210,069,988
600 11,103,727,321

[Jo March]

1. Wow. I like seeing that - I can easily reference that stat

in conversations with my local freeper types here who just think that it's all a big coincidence that the majority of glitches favored Bush.

[TruthIsAll]

32. 1000 RANDOM COIN TOSSES: 498 Heads

	Total Heads in 1000 random coin tosses:	498																		
		1-100				101-200			201-300			301-400			401-500								
0.52	heads	1	0.98	heads	0.81	1	heads	0.46	1	tails	0.81	1	heads	0.55	1								
0.82	heads	1	0.71	heads	0.55	1	heads	0.48	1	tails	0.77	1	heads	0.34	1								1-BINOMDIST(600,1000,0.5,TRUE)
0.86	heads	1	0.64	heads	0.16	1	tails	0.09	1	tails	0.39	1	tails	0.24	1								0.0000000000900598
0.18	tails	0	0.37	tails	0.75	0	heads	0.43	0	tails	0.13	0	tails	0.44	0								11,103,727,321
0.68	heads	1	0.41	tails	0.37	0	tails	0.55	0	heads	0.22	0	tails	0.89	0								
0.03	tails	0	0.08	tails	0.35	0	tails	0.02	0	tails	0.55	0	heads	0.76	0							500	2
0.78	heads	1	0.23	tails	0.06	0	tails	0.40	0	tails	0.87	0	heads	0.12	0							510	4
0.22	tails	0	0.70	heads	0.22	1	tails	0.55	1	heads	0.70	1	heads	0.42	1							520	10
0.21	tails	0	0.96	heads	0.36	1	tails	0.38	1	tails	0.38	1	tails	0.24	1							530	37
0.56	heads	1	0.16	tails	0.43	0	tails	0.73	0	heads	0.09	0	tails	0.16	0							540	193
0.91	heads	1	0.72	heads	0.87	1	heads	0.98	1	heads	0.87	1	heads	0.43	1							550	1,437
0.75	heads	1	0.50	heads	0.45	1	tails	0.93	1	heads	0.23	1	tails	0.30	1							560	15,654
0.05	tails	0	0.89	heads	0.85	1	heads	0.76	1	heads	0.37	1	tails	0.17	1							570	250,812
0.68	heads	1	0.34	tails	0.66	0	heads	0.17	0	tails	0.09	0	tails	0.55	0							580	5,949,049
0.96	heads	1	0.90	heads	0.51	1	heads	0.42	1	tails	0.09	1	tails	0.20	1							590	210,069,988
0.67	heads	1	0.15	tails	0.58	0	heads	0.62	0	heads	0.04	0	tails	0.04	0							600	11,103,727,321
0.83	heads	1	0.25	tails	0.71	0	heads	0.90	0	heads	0.73	0	heads	0.03	0								
0.57	heads	1	0.86	heads	0.33	1	tails	0.52	1	heads	0.74	1	heads	0.54	1								
0.26	tails	0	0.55	heads	0.29	1	tails	0.73	1	heads	0.15	1	tails	0.72	1								
0.71	heads	1	0.42	tails	0.99	0	heads	0.15	0	tails	0.39	0	tails	0.74	0								
0.63	heads	1	0.29	tails	0.76	0	heads	0.82	0	heads	0.78	0	heads	0.91	0								
0.15	tails	0	0.44	tails	0.68	0	heads	0.07	0	tails	0.59	0	heads	0.41	0								
0.42	tails	0	0.91	heads	0.33	1	tails	0.77	1	heads	0.67	1	heads	0.84	1								
0.55	heads	1	0.73	heads	0.23	1	tails	0.15	1	tails	0.18	1	tails	0.93	1								
0.82	heads	1	0.92	heads	0.11	1	tails	0.89	1	heads	0.75	1	heads	0.89	1								
0.29	tails	0	0.33	tails	0.14	0	tails	0.94	0	heads	0.59	0	heads	0.33	0								
0.82	heads	1	0.70	heads	0.15	1	tails	0.03	1	tails	0.46	1	tails	0.48	1								
0.41	tails	0	0.20	tails	0.36	0	tails	0.58	0	heads	0.32	0	tails	0.36	0								
0.90	heads	1	0.27	tails	0.35	0	tails	0.56	0	heads	0.52	0	heads	0.01	0								
0.37	tails	0	0.50	heads	0.38	1	tails	0.06	1	tails	0.70	1	heads	0.50	1								
0.36	tails	0	0.62	heads	0.27	1	tails	0.50	1	tails	0.08	1	tails	0.59	1
0.01	tails	0	0.54	heads	0.46	1	tails	0.94	1	heads	0.95	1	heads	0.21	1
0.42	tails	0	0.46	tails	0.84	0	heads	0.70	0	heads	0.51	0	heads	0.46	0
0.63	heads	1	0.49	tails	0.13	0	tails	0.14	0	tails	0.46	0	tails	0.96	0
0.53	heads	1	0.24	tails	0.88	0	heads	0.18	0	tails	0.94	0	heads	0.16	0
0.29	tails	0	0.34	tails	0.05	0	tails	0.24	0	tails	0.67	0	heads	0.09	0
0.78	heads	1	0.16	tails	0.60	0	heads	0.39	0	tails	0.14	0	tails	0.43	0
0.11	tails	0	0.42	tails	0.96	0	heads	0.98	0	heads	0.81	0	heads	0.49	0
0.07	tails	0	0.81	heads	0.62	1	heads	0.17	1	tails	0.65	1	heads	0.35	1
0.51	heads	1	0.58	heads	0.35	1	tails	0.20	1	tails	0.72	1	heads	0.43	1
0.53	heads	1	0.49	tails	0.62	0	heads	0.77	0	heads	0.66	0	heads	0.78	0
0.87	heads	1	0.35	tails	0.86	0	heads	0.85	0	heads	0.11	0	tails	0.39	0
0.62	heads	1	0.50	heads	0.96	1	heads	0.65	1	heads	0.73	1	heads	0.64	1
0.42	tails	0	0.93	heads	0.59	1	heads	0.30	1	tails	0.61	1	heads	0.07	1
0.57	heads	1	0.62	heads	0.51	1	heads	0.64	1	heads	0.43	1	tails	0.39	1
0.63	heads	1	0.09	tails	0.88	0	heads	0.73	0	heads	0.94	0	heads	0.35	0
0.89	heads	1	0.17	tails	0.32	0	tails	0.85	0	heads	0.32	0	tails	0.04	0
0.68	heads	1	0.44	tails	0.20	0	tails	0.24	0	tails	0.38	0	tails	0.08	0
0.43	tails	0	0.70	heads	0.48	1	tails	0.19	1	tails	0.70	1	heads	0.65	1
0.03	tails	0	0.36	tails	0.15	0	tails	0.63	0	heads	0.14	0	tails	0.09	0
0.19	tails	0	0.77	heads	0.54	1	heads	0.84	1	heads	0.57	1	heads	0.06	1
0.77	heads	1	0.02	tails	0.67	0	heads	0.28	0	tails	0.99	0	heads	0.73	0
0.55	heads	1	0.85	heads	0.99	1	heads	0.29	1	tails	0.43	1	tails	0.27	1
0.27	tails	0	0.31	tails	0.87	0	heads	0.21	0	tails	0.68	0	heads	0.74	0
0.86	heads	1	0.39	tails	0.61	0	heads	0.70	0	heads	0.68	0	heads	0.03	0
0.64	heads	1	0.74	heads	0.53	1	heads	0.30	1	tails	0.38	1	tails	0.67	1
0.91	heads	1	0.04	tails	0.90	0	heads	0.23	0	tails	0.40	0	tails	0.34	0
0.94	heads	1	0.03	tails	0.35	0	tails	0.87	0	heads	0.85	0	heads	0.29	0
0.27	tails	0	0.70	heads	0.36	1	tails	0.40	1	tails	0.27	1	tails	0.70	1
0.47	tails	0	0.63	heads	0.81	1	heads	0.46	1	tails	0.97	1	heads	0.92	1
0.01	tails	0	0.11	tails	0.02	0	tails	0.14	0	tails	0.96	0	heads	0.05	0
0.65	heads	1	0.50	tails	0.09	0	tails	0.50	0	tails	0.18	0	tails	0.19	0
0.98	heads	1	0.11	tails	0.49	0	tails	0.86	0	heads	0.79	0	heads	0.47	0
0.01	tails	0	0.86	heads	0.54	1	heads	0.04	1	tails	0.15	1	tails	0.94	1
0.76	heads	1	0.03	tails	0.36	0	tails	0.94	0	heads	0.20	0	tails	0.77	0
0.52	heads	1	0.99	heads	0.07	1	tails	0.72	1	heads	0.43	1	tails	0.44	1
0.69	heads	1	0.22	tails	0.41	0	tails	0.92	0	heads	0.01	0	tails	0.66	0
0.14	tails	0	0.44	tails	0.46	0	tails	0.65	0	heads	0.96	0	heads	0.38	0
0.12	tails	0	0.48	tails	0.89	0	heads	0.25	0	tails	0.82	0	heads	0.07	0
0.67	heads	1	0.56	heads	0.95	1	heads	0.35	1	tails	0.53	1	heads	0.82	1
0.77	heads	1	0.26	tails	0.99	0	heads	0.99	0	heads	0.65	0	heads	0.75	0
0.17	tails	0	0.04	tails	0.16	0	tails	0.18	0	tails	0.14	0	tails	0.71	0
0.25	tails	0	0.06	tails	0.74	0	heads	0.46	0	tails	0.13	0	tails	0.34	0
0.78	heads	1	0.94	heads	0.01	1	tails	0.44	1	tails	0.49	1	tails	0.29	1
0.14	tails	0	0.57	heads	0.68	1	heads	0.46	1	tails	0.19	1	tails	0.39	1
0.92	heads	1	0.72	heads	0.92	1	heads	0.31	1	tails	0.76	1	heads	0.53	1
0.26	tails	0	0.54	heads	0.57	1	heads	0.61	1	heads	0.56	1	heads	0.35	1
0.57	heads	1	0.17	tails	0.92	0	heads	0.75	0	heads	0.34	0	tails	0.30	0
0.08	tails	0	0.74	heads	0.86	1	heads	0.44	1	tails	0.99	1	heads	0.92	1
0.74	heads	1	0.48	tails	0.68	0	heads	0.48	0	tails	0.32	0	tails	0.63	0
0.74	heads	1	0.90	heads	0.77	1	heads	0.58	1	heads	0.95	1	heads	0.04	1
0.78	heads	1	0.57	heads	0.40	1	tails	0.07	1	tails	0.63	1	heads	0.64	1
0.06	tails	0	0.39	tails	0.19	0	tails	0.89	0	heads	0.89	0	heads	0.77	0
0.82	heads	1	0.65	heads	0.79	1	heads	0.95	1	heads	0.65	1	heads	0.85	1
0.64	heads	1	0.14	tails	0.31	0	tails	0.13	0	tails	0.25	0	tails	0.40	0
0.86	heads	1	0.47	tails	0.36	0	tails	0.16	0	tails	0.58	0	heads	0.51	0
0.73	heads	1	0.69	heads	0.52	1	heads	0.26	1	tails	0.92	1	heads	0.61	1
0.80	heads	1	0.06	tails	0.12	0	tails	0.80	0	heads	0.78	0	heads	0.94	0
0.60	heads	1	0.40	tails	0.44	0	tails	0.43	0	tails	0.98	0	heads	0.84	0
0.91	heads	1	0.67	heads	0.05	1	tails	0.70	1	heads	0.07	1	tails	0.35	1
0.32	tails	0	0.29	tails	0.78	0	heads	0.64	0	heads	0.57	0	heads	0.01	0
0.39	tails	0	0.16	tails	0.16	0	tails	0.37	0	tails	0.38	0	tails	0.94	0
0.72	heads	1	0.42	tails	0.54	0	heads	0.44	0	tails	0.66	0	heads	0.66	0
0.21	tails	0	0.12	tails	0.53	0	heads	0.61	0	heads	0.73	0	heads	0.38	0
0.53	heads	1	0.65	heads	0.12	1	tails	0.12	1	tails	0.05	1	tails	0.40	1
0.87	heads	1	0.12	tails	0.31	0	tails	0.73	0	heads	0.11	0	tails	0.01	0
0.01	tails	0	0.52	heads	0.66	1	heads	0.26	1	tails	0.46	1	tails	0.62	1
0.77	heads	1	0.34	tails	0.06	0	tails	0.15	0	tails	0.98	0	heads	0.52	0
0.34	tails	0	0.57	heads	0.62	1	heads	0.82	1	heads	0.32	1	tails	0.73	1
0.71	heads	1	0.72	heads	0.80	1	heads	0.52	1	heads	0.41	1	tails	0.40	1
															
245	total	61				46			46			46			46
															
		501-600				601-700			701-800			801-900			901-1000
0.94	heads	1	heads	0.50	heads	1	0.17	tails	0	0.87	heads	1	heads	0.42	1
0.35	tails	0	tails	0.20	tails	0	0.48	tails	0	0.32	tails	0	heads	0.95	0
0.89	heads	1	heads	0.70	heads	1	0.27	tails	0	0.57	heads	1	heads	0.70	1
0.55	heads	1	heads	0.93	heads	1	0.81	heads	1	0.69	heads	1	heads	0.74	1
0.84	heads	1	heads	0.72	heads	1	0.95	heads	1	0.35	tails	0	heads	0.10	0
0.27	tails	0	tails	0.09	tails	0	0.15	tails	0	0.99	heads	1	heads	0.86	1
0.24	tails	0	tails	0.00	tails	0	0.44	tails	0	0.15	tails	0	heads	0.65	0
0.11	tails	0	tails	0.11	tails	0	0.60	heads	1	0.37	tails	0	heads	0.13	0
0.50	tails	0	tails	0.78	heads	1	0.44	tails	0	0.22	tails	0	heads	0.85	0
0.55	heads	1	heads	0.92	heads	1	0.78	heads	1	0.31	tails	0	heads	0.43	0
0.79	heads	1	heads	0.32	tails	0	0.72	heads	1	0.72	heads	1	heads	0.29	1
0.13	tails	0	tails	0.72	heads	1	0.81	heads	1	0.60	heads	1	heads	0.57	1
0.48	tails	0	tails	0.72	heads	1	0.17	tails	0	0.18	tails	0	heads	0.92	0
0.18	tails	0	tails	0.33	tails	0	0.43	tails	0	0.04	tails	0	heads	0.63	0
0.87	heads	1	heads	0.76	heads	1	0.11	tails	0	0.01	tails	0	heads	0.38	0
0.51	heads	1	heads	0.06	tails	0	0.77	heads	1	0.02	tails	0	heads	0.35	0
0.53	heads	1	heads	0.52	heads	1	0.41	tails	0	0.27	tails	0	heads	0.89	0
0.53	heads	1	heads	0.66	heads	1	0.75	heads	1	0.50	tails	0	heads	0.37	0
0.10	tails	0	tails	0.05	tails	0	0.09	tails	0	0.03	tails	0	heads	0.56	0
0.34	tails	0	tails	0.34	tails	0	0.13	tails	0	0.33	tails	0	heads	0.83	0
0.95	heads	1	heads	0.09	tails	0	0.88	heads	1	0.05	tails	0	heads	0.20	0
0.03	tails	0	tails	0.79	heads	1	0.49	tails	0	0.53	heads	1	heads	0.48	1
0.18	tails	0	tails	0.24	tails	0	0.59	heads	1	0.35	tails	0	heads	0.20	0
0.33	tails	0	tails	0.02	tails	0	0.72	heads	1	0.05	tails	0	heads	0.83	0
0.17	tails	0	tails	0.67	heads	1	0.68	heads	1	0.70	heads	1	heads	0.15	1
0.52	heads	1	heads	0.15	tails	0	0.00	tails	0	0.74	heads	1	heads	0.40	1
0.53	heads	1	heads	0.17	tails	0	0.11	tails	0	0.65	heads	1	heads	0.45	1
0.48	tails	0	tails	0.57	heads	1	0.23	tails	0	0.10	tails	0	heads	0.07	0
0.32	tails	0	tails	0.44	tails	0	0.20	tails	0	0.75	heads	1	heads	0.57	1
0.80	heads	1	heads	0.20	tails	0	0.07	tails	0	0.65	heads	1	heads	0.59	1
0.82	heads	1	heads	0.47	tails	0	0.05	tails	0	0.69	heads	1	heads	0.92	1
0.85	heads	1	heads	0.29	tails	0	0.60	heads	1	0.96	heads	1	heads	0.41	1
0.63	heads	1	heads	0.56	heads	1	0.15	tails	0	0.99	heads	1	heads	0.82	1
0.35	tails	0	tails	0.34	tails	0	0.77	heads	1	0.77	heads	1	heads	0.77	1
0.73	heads	1	heads	0.58	heads	1	0.89	heads	1	0.78	heads	1	heads	0.66	1
0.76	heads	1	heads	0.60	heads	1	0.73	heads	1	0.99	heads	1	heads	0.34	1
0.65	heads	1	heads	0.61	heads	1	0.61	heads	1	0.94	heads	1	heads	0.78	1
0.51	heads	1	heads	0.65	heads	1	0.35	tails	0	0.23	tails	0	heads	0.78	0
0.86	heads	1	heads	0.56	heads	1	0.56	heads	1	0.70	heads	1	heads	0.89	1
0.93	heads	1	heads	0.67	heads	1	0.44	tails	0	0.20	tails	0	heads	0.70	0
0.05	tails	0	tails	0.61	heads	1	0.54	heads	1	0.88	heads	1	heads	0.62	1
0.31	tails	0	tails	0.65	heads	1	0.98	heads	1	0.11	tails	0	heads	0.61	0
0.99	heads	1	heads	0.74	heads	1	0.39	tails	0	0.28	tails	0	heads	0.27	0
0.43	tails	0	tails	0.05	tails	0	0.62	heads	1	0.12	tails	0	heads	0.76	0
0.95	heads	1	heads	0.44	tails	0	0.79	heads	1	0.35	tails	0	heads	0.38	0
0.42	tails	0	tails	0.52	heads	1	0.06	tails	0	0.73	heads	1	heads	0.59	1
0.33	tails	0	tails	0.19	tails	0	0.52	heads	1	0.89	heads	1	heads	0.06	1
0.54	heads	1	heads	0.69	heads	1	0.36	tails	0	0.02	tails	0	heads	0.09	0
0.42	tails	0	tails	0.34	tails	0	0.64	heads	1	0.23	tails	0	heads	0.46	0
0.60	heads	1	heads	0.39	tails	0	0.39	tails	0	0.56	heads	1	heads	0.94	1
0.71	heads	1	heads	0.55	heads	1	0.72	heads	1	0.24	tails	0	heads	0.28	0
0.56	heads	1	heads	0.04	tails	0	0.92	heads	1	0.83	heads	1	heads	0.49	1
0.99	heads	1	heads	0.66	heads	1	0.44	tails	0	0.20	tails	0	heads	0.59	0
0.11	tails	0	tails	0.37	tails	0	0.94	heads	1	0.34	tails	0	heads	0.84	0
0.24	tails	0	tails	0.31	tails	0	0.83	heads	1	0.01	tails	0	heads	0.05	0
0.09	tails	0	tails	0.93	heads	1	0.61	heads	1	0.21	tails	0	heads	0.64	0
0.47	tails	0	tails	0.07	tails	0	0.11	tails	0	0.63	heads	1	heads	0.03	1
0.77	heads	1	heads	0.26	tails	0	0.63	heads	1	0.19	tails	0	heads	0.41	0
0.40	tails	0	tails	0.92	heads	1	0.82	heads	1	0.68	heads	1	heads	0.84	1
0.17	tails	0	tails	0.65	heads	1	0.34	tails	0	0.13	tails	0	heads	0.60	0
0.17	tails	0	tails	0.83	heads	1	0.41	tails	0	0.43	tails	0	heads	0.71	0
0.87	heads	1	heads	0.72	heads	1	0.30	tails	0	0.35	tails	0	heads	0.34	0
0.33	tails	0	tails	0.12	tails	0	0.78	heads	1	0.72	heads	1	heads	0.74	1
0.99	heads	1	heads	0.58	heads	1	0.71	heads	1	0.47	tails	0	heads	0.33	0
0.33	tails	0	tails	0.34	tails	0	0.59	heads	1	0.58	heads	1	heads	0.12	1
0.68	heads	1	heads	0.73	heads	1	0.82	heads	1	0.01	tails	0	heads	0.31	0
0.22	tails	0	tails	0.26	tails	0	0.34	tails	0	0.75	heads	1	heads	0.64	1
0.53	heads	1	heads	0.60	heads	1	0.92	heads	1	0.38	tails	0	heads	0.14	0
0.47	tails	0	tails	0.54	heads	1	0.52	heads	1	0.64	heads	1	heads	0.74	1
0.57	heads	1	heads	0.66	heads	1	0.26	tails	0	0.94	heads	1	heads	0.79	1
0.20	tails	0	tails	0.89	heads	1	0.68	heads	1	0.85	heads	1	heads	0.14	1
0.98	heads	1	heads	0.45	tails	0	0.88	heads	1	0.77	heads	1	heads	0.60	1
0.87	heads	1	heads	0.99	heads	1	0.07	tails	0	0.87	heads	1	heads	0.46	1
0.92	heads	1	heads	0.72	heads	1	0.06	tails	0	0.93	heads	1	heads	0.44	1
0.22	tails	0	tails	0.22	tails	0	0.77	heads	1	0.58	heads	1	heads	0.79	1
0.85	heads	1	heads	0.85	heads	1	0.87	heads	1	0.51	heads	1	heads	0.33	1
0.27	tails	0	tails	0.16	tails	0	0.89	heads	1	0.50	tails	0	heads	0.17	0
0.74	heads	1	heads	0.27	tails	0	0.03	tails	0	0.77	heads	1	heads	0.68	1
0.20	tails	0	tails	0.21	tails	0	0.07	tails	0	0.22	tails	0	heads	0.90	0
0.84	heads	1	heads	0.93	heads	1	0.12	tails	0	0.15	tails	0	heads	0.62	0
0.55	heads	1	heads	0.43	tails	0	0.97	heads	1	0.07	tails	0	heads	0.08	0
0.40	tails	0	tails	0.90	heads	1	0.24	tails	0	0.87	heads	1	heads	0.54	1
0.97	heads	1	heads	0.79	heads	1	0.51	heads	1	0.83	heads	1	heads	0.91	1
0.03	tails	0	tails	0.19	tails	0	0.31	tails	0	0.70	heads	1	heads	0.97	1
0.52	heads	1	heads	0.93	heads	1	0.04	tails	0	0.46	tails	0	heads	0.22	0
0.41	tails	0	tails	0.45	tails	0	0.06	tails	0	0.35	tails	0	heads	0.58	0
0.53	heads	1	heads	0.78	heads	1	0.86	heads	1	0.13	tails	0	heads	0.83	0
0.70	heads	1	heads	0.93	heads	1	0.92	heads	1	0.74	heads	1	heads	0.37	1
0.87	heads	1	heads	0.88	heads	1	0.42	tails	0	0.27	tails	0	heads	0.18	0
0.17	tails	0	tails	0.66	heads	1	0.40	tails	0	0.98	heads	1	heads	0.14	1
0.25	tails	0	tails	0.47	tails	0	0.79	heads	1	0.63	heads	1	heads	0.43	1
0.64	heads	1	heads	0.04	tails	0	0.79	heads	1	0.79	heads	1	heads	0.75	1
0.90	heads	1	heads	0.35	tails	0	0.15	tails	0	0.37	tails	0	heads	0.21	0
0.87	heads	1	heads	0.62	heads	1	0.79	heads	1	0.42	tails	0	heads	0.67	0
0.41	tails	0	tails	0.09	tails	0	0.06	tails	0	0.97	heads	1	heads	0.42	1
0.47	tails	0	tails	0.54	heads	1	0.20	tails	0	0.67	heads	1	heads	0.65	1
0.78	heads	1	heads	0.77	heads	1	0.34	tails	0	0.21	tails	0	heads	0.30	0
0.15	tails	0	tails	0.19	tails	0	0.22	tails	0	0.27	tails	0	heads	0.01	0
0.72	heads	1	heads	0.18	tails	0	0.14	tails	0	0.00	tails	0	heads	0.51	0
0.84	heads	1	heads	0.82	heads	1	0.09	tails	0	0.19	tails	0	heads	0.43	0
															
253	total	54				54			49			48			48

[TruthIsAll]

38. I referenced the wrong column at the far right (all Heads). Totals are OK

Here's another run:

	Total Heads in 1000 random coin tosses:	498					
														
1			2			3			4			5		
														
0.93	heads	1	0.86	heads	1	0.45	tails	0	0.75	heads	1	0.37	tails	0
0.94	heads	1	0.43	tails	0	0.39	tails	0	0.16	tails	0	0.36	tails	0
0.30	tails	0	0.18	tails	0	0.31	tails	0	0.97	heads	1	0.01	tails	0
0.63	heads	1	0.36	tails	0	0.29	tails	0	0.32	tails	0	0.22	tails	0
0.24	tails	0	0.99	heads	1	0.03	tails	0	0.93	heads	1	0.36	tails	0
0.83	heads	1	0.31	tails	0	0.47	tails	0	0.15	tails	0	0.67	heads	1
0.10	tails	0	0.97	heads	1	0.35	tails	0	0.67	heads	1	0.11	tails	0
0.15	tails	0	0.36	tails	0	0.68	heads	1	0.26	tails	0	0.06	tails	0
0.79	heads	1	0.41	tails	0	0.90	heads	1	0.96	heads	1	0.03	tails	0
0.39	tails	0	0.71	heads	1	0.61	heads	1	0.67	heads	1	0.66	heads	1
0.33	tails	0	0.87	heads	1	0.27	tails	0	0.46	tails	0	0.46	tails	0
0.57	heads	1	0.30	tails	0	0.88	heads	1	0.09	tails	0	0.84	heads	1
0.78	heads	1	0.75	heads	1	0.05	tails	0	0.01	tails	0	0.42	tails	0
0.87	heads	1	0.20	tails	0	0.25	tails	0	0.11	tails	0	0.48	tails	0
0.55	heads	1	0.30	tails	0	0.63	heads	1	0.45	tails	0	0.85	heads	1
0.18	tails	0	0.65	heads	1	0.84	heads	1	0.80	heads	1	0.73	heads	1
0.52	heads	1	0.83	heads	1	0.95	heads	1	0.86	heads	1	0.54	heads	1
0.72	heads	1	0.77	heads	1	0.96	heads	1	0.56	heads	1	0.96	heads	1
0.05	tails	0	0.92	heads	1	0.81	heads	1	0.48	tails	0	0.17	tails	0
0.36	tails	0	0.67	heads	1	0.93	heads	1	0.13	tails	0	0.93	heads	1
0.23	tails	0	0.45	tails	0	0.69	heads	1	0.06	tails	0	0.80	heads	1
0.72	heads	1	0.98	heads	1	0.56	heads	1	0.18	tails	0	0.14	tails	0
0.98	heads	1	0.97	heads	1	0.96	heads	1	0.93	heads	1	0.03	tails	0
0.68	heads	1	0.97	heads	1	0.42	tails	0	0.94	heads	1	0.41	tails	0
0.35	tails	0	0.00	tails	0	0.72	heads	1	0.75	heads	1	0.02	tails	0
0.88	heads	1	0.77	heads	1	0.99	heads	1	0.02	tails	0	0.96	heads	1
0.26	tails	0	0.96	heads	1	0.70	heads	1	0.66	heads	1	0.91	heads	1
0.83	heads	1	0.67	heads	1	0.20	tails	0	0.22	tails	0	0.45	tails	0
0.97	heads	1	0.45	tails	0	0.24	tails	0	0.87	heads	1	0.89	heads	1
0.47	tails	0	0.76	heads	1	0.51	heads	1	0.14	tails	0	0.49	tails	0
0.74	heads	1	0.10	tails	0	0.09	tails	0	0.16	tails	0	0.63	heads	1
0.03	tails	0	0.66	heads	1	0.11	tails	0	0.80	heads	1	0.70	heads	1
0.50	heads	1	0.90	heads	1	0.58	heads	1	0.12	tails	0	0.97	heads	1
0.43	tails	0	0.65	heads	1	0.26	tails	0	0.24	tails	0	0.62	heads	1
0.01	tails	0	0.02	tails	0	0.52	heads	1	0.45	tails	0	0.91	heads	1
0.93	heads	1	0.10	tails	0	0.54	heads	1	0.68	heads	1	0.06	tails	0
0.37	tails	0	0.81	heads	1	0.17	tails	0	0.56	heads	1	0.89	heads	1
0.48	tails	0	0.60	heads	1	0.46	tails	0	0.03	tails	0	0.84	heads	1
0.39	tails	0	0.45	tails	0	0.23	tails	0	0.77	heads	1	0.26	tails	0
0.01	tails	0	0.91	heads	1	0.10	tails	0	0.07	tails	0	0.50	heads	1
0.57	heads	1	0.64	heads	1	0.39	tails	0	0.76	heads	1	0.93	heads	1
0.24	tails	0	0.05	tails	0	0.77	heads	1	0.17	tails	0	0.14	tails	0
0.00	tails	0	0.80	heads	1	0.63	heads	1	0.56	heads	1	0.09	tails	0
0.65	heads	1	0.37	tails	0	0.35	tails	0	0.33	tails	0	0.10	tails	0
0.46	tails	0	0.67	heads	1	0.26	tails	0	0.65	heads	1	0.53	heads	1
0.10	tails	0	0.93	heads	1	0.32	tails	0	0.37	tails	0	0.87	heads	1
0.71	heads	1	0.47	tails	0	0.74	heads	1	0.94	heads	1	0.79	heads	1
0.37	tails	0	0.78	heads	1	0.49	tails	0	0.24	tails	0	0.01	tails	0
0.99	heads	1	0.82	heads	1	0.47	tails	0	0.24	tails	0	0.23	tails	0
0.33	tails	0	0.14	tails	0	0.73	heads	1	0.05	tails	0	0.92	heads	1
0.44	tails	0	0.18	tails	0	0.01	tails	0	0.23	tails	0	0.33	tails	0
0.10	tails	0	0.40	tails	0	0.60	heads	1	0.21	tails	0	0.77	heads	1
0.01	tails	0	0.70	heads	1	0.76	heads	1	0.30	tails	0	0.06	tails	0
0.31	tails	0	0.81	heads	1	0.71	heads	1	0.72	heads	1	0.57	heads	1
0.02	tails	0	0.34	tails	0	0.78	heads	1	0.80	heads	1	0.72	heads	1
0.00	tails	0	0.00	tails	0	0.85	heads	1	0.30	tails	0	0.83	heads	1
0.51	heads	1	0.34	tails	0	0.48	tails	0	0.56	heads	1	0.45	tails	0
0.81	heads	1	0.46	tails	0	0.53	heads	1	0.26	tails	0	0.64	heads	1
0.55	heads	1	0.01	tails	0	0.93	heads	1	0.71	heads	1	0.36	tails	0
0.78	heads	1	0.84	heads	1	0.96	heads	1	0.27	tails	0	0.68	heads	1
0.02	tails	0	0.47	tails	0	0.76	heads	1	0.88	heads	1	0.84	heads	1
0.82	heads	1	0.13	tails	0	0.73	heads	1	0.43	tails	0	0.04	tails	0
0.65	heads	1	0.38	tails	0	0.43	tails	0	0.03	tails	0	0.80	heads	1
0.02	tails	0	0.24	tails	0	0.74	heads	1	0.94	heads	1	0.26	tails	0
0.35	tails	0	0.93	heads	1	0.03	tails	0	0.91	heads	1	0.29	tails	0
0.52	heads	1	0.79	heads	1	0.35	tails	0	0.57	heads	1	0.72	heads	1
0.53	heads	1	0.40	tails	0	0.09	tails	0	0.88	heads	1	0.24	tails	0
0.01	tails	0	0.89	heads	1	1.00	heads	1	0.36	tails	0	0.97	heads	1
0.22	tails	0	0.92	heads	1	0.84	heads	1	0.59	heads	1	0.85	heads	1
0.90	heads	1	0.71	heads	1	0.34	tails	0	0.35	tails	0	0.67	heads	1
0.80	heads	1	0.91	heads	1	0.11	tails	0	0.92	heads	1	0.66	heads	1
0.90	heads	1	0.69	heads	1	0.03	tails	0	0.66	heads	1	0.63	heads	1
0.38	tails	0	0.92	heads	1	0.42	tails	0	0.78	heads	1	0.79	heads	1
0.02	tails	0	0.01	tails	0	0.21	tails	0	0.95	heads	1	0.36	tails	0
0.20	tails	0	0.75	heads	1	0.10	tails	0	0.02	tails	0	0.29	tails	0
0.47	tails	0	0.81	heads	1	0.96	heads	1	0.09	tails	0	0.07	tails	0
0.97	heads	1	0.68	heads	1	0.13	tails	0	0.57	heads	1	0.66	heads	1
0.94	heads	1	0.68	heads	1	0.33	tails	0	0.39	tails	0	0.05	tails	0
0.53	heads	1	0.54	heads	1	0.38	tails	0	0.49	tails	0	0.21	tails	0
0.44	tails	0	1.00	heads	1	0.57	heads	1	0.59	heads	1	0.44	tails	0
0.52	heads	1	0.04	tails	0	0.88	heads	1	0.09	tails	0	0.34	tails	0
0.47	tails	0	0.24	tails	0	0.28	tails	0	0.41	tails	0	0.05	tails	0
0.68	heads	1	0.02	tails	0	0.83	heads	1	0.02	tails	0	0.71	heads	1
0.88	heads	1	0.03	tails	0	0.33	tails	0	0.26	tails	0	1.00	heads	1
0.64	heads	1	0.33	tails	0	0.22	tails	0	0.69	heads	1	0.19	tails	0
0.55	heads	1	0.50	tails	0	0.56	heads	1	0.78	heads	1	0.94	heads	1
0.34	tails	0	0.02	tails	0	0.55	heads	1	0.79	heads	1	0.35	tails	0
0.55	heads	1	0.69	heads	1	0.46	tails	0	0.28	tails	0	0.76	heads	1
0.48	tails	0	0.21	tails	0	0.94	heads	1	0.29	tails	0	0.24	tails	0
0.70	heads	1	0.47	tails	0	0.28	tails	0	0.90	heads	1	0.05	tails	0
0.26	tails	0	0.60	heads	1	0.83	heads	1	0.48	tails	0	0.82	heads	1
0.32	tails	0	0.94	heads	1	0.03	tails	0	0.83	heads	1	0.74	heads	1
0.54	heads	1	0.27	tails	0	0.73	heads	1	0.65	heads	1	0.46	tails	0
0.06	tails	0	0.69	heads	1	0.37	tails	0	0.97	heads	1	0.78	heads	1
0.54	heads	1	0.40	tails	0	0.37	tails	0	0.33	tails	0	0.05	tails	0
0.71	heads	1	0.42	tails	0	0.14	tails	0	0.38	tails	0	0.83	heads	1
0.06	tails	0	0.30	tails	0	0.79	heads	1	0.28	tails	0	0.26	tails	0
0.55	heads	1	0.89	heads	1	0.45	tails	0	0.54	heads	1	0.59	heads	1
0.05	tails	0	0.43	tails	0	0.76	heads	1	0.00	tails	0	0.66	heads	1
0.24	tails	0	0.88	heads	1	0.56	heads	1	0.41	tails	0	0.26	tails	0
														
248	total	49			53			49			46			51
														
5			7			8			9			10		
0.71	heads	1	0.59	heads	1	0.77	heads	1	0.83	heads	1	0.12	tails	0
0.16	tails	0	0.08	tails	0	0.31	tails	0	0.14	tails	0	0.75	heads	1
0.65	heads	1	0.31	tails	0	0.20	tails	0	0.70	heads	1	1.00	heads	1
0.64	heads	1	0.06	tails	0	0.01	tails	0	0.51	heads	1	0.67	heads	1
0.65	heads	1	0.02	tails	0	0.85	heads	1	0.93	heads	1	0.80	heads	1
0.67	heads	1	0.25	tails	0	0.06	tails	0	0.39	tails	0	0.79	heads	1
0.14	tails	0	0.23	tails	0	0.96	heads	1	0.10	tails	0	0.73	heads	1
0.91	heads	1	0.80	heads	1	0.89	heads	1	0.89	heads	1	0.70	heads	1
0.33	tails	0	0.79	heads	1	0.48	tails	0	0.54	heads	1	0.42	tails	0
0.01	tails	0	0.97	heads	1	0.74	heads	1	0.66	heads	1	0.52	heads	1
0.09	tails	0	0.28	tails	0	0.02	tails	0	0.48	tails	0	0.86	heads	1
0.08	tails	0	0.69	heads	1	0.81	heads	1	0.50	tails	0	0.94	heads	1
0.13	tails	0	0.76	heads	1	0.34	tails	0	0.26	tails	0	0.61	heads	1
0.24	tails	0	0.22	tails	0	0.83	heads	1	0.81	heads	1	0.11	tails	0
0.00	tails	0	0.67	heads	1	0.50	heads	1	0.56	heads	1	0.63	heads	1
0.15	tails	0	0.31	tails	0	0.29	tails	0	0.49	tails	0	0.04	tails	0
0.73	heads	1	0.72	heads	1	0.81	heads	1	1.00	heads	1	0.77	heads	1
0.89	heads	1	0.22	tails	0	0.88	heads	1	0.27	tails	0	0.01	tails	0
0.24	tails	0	0.66	heads	1	0.85	heads	1	0.46	tails	0	0.69	heads	1
0.74	heads	1	0.97	heads	1	0.28	tails	0	0.95	heads	1	0.44	tails	0
0.86	heads	1	0.09	tails	0	0.14	tails	0	0.60	heads	1	0.49	tails	0
0.89	heads	1	0.74	heads	1	0.64	heads	1	0.66	heads	1	0.94	heads	1
0.65	heads	1	0.32	tails	0	0.93	heads	1	0.36	tails	0	0.03	tails	0
0.15	tails	0	0.09	tails	0	0.86	heads	1	0.33	tails	0	0.25	tails	0
0.87	heads	1	0.05	tails	0	0.15	tails	0	0.14	tails	0	0.80	heads	1
0.62	heads	1	0.11	tails	0	0.30	tails	0	0.63	heads	1	0.53	heads	1
0.36	tails	0	0.24	tails	0	0.76	heads	1	0.04	tails	0	0.26	tails	0
0.58	heads	1	0.70	heads	1	0.27	tails	0	0.07	tails	0	0.88	heads	1
0.13	tails	0	0.37	tails	0	0.21	tails	0	0.66	heads	1	0.83	heads	1
0.67	heads	1	0.22	tails	0	0.47	tails	0	0.76	heads	1	0.92	heads	1
0.40	tails	0	0.49	tails	0	0.12	tails	0	0.62	heads	1	0.17	tails	0
0.71	heads	1	0.47	tails	0	0.12	tails	0	0.62	heads	1	0.08	tails	0
0.79	heads	1	0.53	heads	1	0.88	heads	1	0.17	tails	0	0.82	heads	1
0.23	tails	0	0.52	heads	1	0.07	tails	0	0.89	heads	1	0.91	heads	1
0.85	heads	1	0.83	heads	1	0.10	tails	0	0.14	tails	0	0.25	tails	0
0.25	tails	0	0.94	heads	1	0.19	tails	0	0.40	tails	0	0.75	heads	1
0.53	heads	1	0.45	tails	0	0.86	heads	1	0.38	tails	0	0.65	heads	1
0.72	heads	1	0.01	tails	0	0.03	tails	0	0.43	tails	0	0.57	heads	1
0.81	heads	1	0.09	tails	0	0.19	tails	0	0.50	tails	0	0.37	tails	0
0.25	tails	0	0.63	heads	1	0.77	heads	1	0.21	tails	0	0.27	tails	0
0.13	tails	0	0.59	heads	1	0.72	heads	1	0.87	heads	1	0.15	tails	0
0.72	heads	1	0.52	heads	1	0.40	tails	0	1.00	heads	1	0.32	tails	0
0.18	tails	0	0.60	heads	1	0.25	tails	0	0.19	tails	0	0.74	heads	1
0.41	tails	0	0.68	heads	1	0.52	heads	1	0.67	heads	1	0.04	tails	0
0.52	heads	1	0.46	tails	0	0.32	tails	0	0.50	tails	0	0.06	tails	0
0.42	tails	0	0.11	tails	0	0.05	tails	0	0.02	tails	0	0.16	tails	0
0.84	heads	1	0.58	heads	1	0.88	heads	1	0.61	heads	1	0.94	heads	1
0.19	tails	0	0.44	tails	0	0.04	tails	0	0.50	heads	1	0.53	heads	1
0.43	tails	0	0.53	heads	1	0.57	heads	1	0.70	heads	1	0.05	tails	0
0.13	tails	0	0.26	tails	0	0.02	tails	0	0.47	tails	0	0.97	heads	1
0.82	heads	1	0.81	heads	1	0.56	heads	1	0.98	heads	1	0.94	heads	1
0.30	tails	0	0.30	tails	0	0.58	heads	1	0.06	tails	0	0.48	tails	0
0.88	heads	1	0.17	tails	0	0.10	tails	0	0.81	heads	1	0.57	heads	1
0.05	tails	0	0.51	heads	1	0.44	tails	0	0.21	tails	0	0.51	heads	1
0.29	tails	0	0.98	heads	1	0.80	heads	1	0.91	heads	1	0.83	heads	1
0.06	tails	0	0.86	heads	1	0.71	heads	1	0.16	tails	0	0.27	tails	0
0.75	heads	1	0.16	tails	0	0.62	heads	1	0.95	heads	1	0.44	tails	0
0.29	tails	0	0.38	tails	0	0.60	heads	1	0.67	heads	1	0.98	heads	1
0.60	heads	1	0.31	tails	0	0.47	tails	0	0.93	heads	1	0.40	tails	0
0.34	tails	0	0.80	heads	1	0.86	heads	1	0.59	heads	1	0.49	tails	0
0.59	heads	1	0.22	tails	0	0.96	heads	1	0.43	tails	0	0.98	heads	1
0.29	tails	0	0.01	tails	0	0.52	heads	1	0.76	heads	1	0.11	tails	0
0.44	tails	0	0.32	tails	0	0.98	heads	1	0.19	tails	0	0.27	tails	0
0.41	tails	0	0.67	heads	1	0.82	heads	1	0.03	tails	0	0.59	heads	1
0.20	tails	0	0.36	tails	0	0.47	tails	0	0.79	heads	1	0.88	heads	1
0.46	tails	0	0.88	heads	1	0.94	heads	1	0.51	heads	1	0.86	heads	1
0.99	heads	1	0.82	heads	1	0.77	heads	1	0.97	heads	1	0.35	tails	0
0.85	heads	1	0.66	heads	1	0.84	heads	1	0.84	heads	1	0.95	heads	1
0.20	tails	0	0.24	tails	0	0.13	tails	0	0.81	heads	1	0.74	heads	1
0.57	heads	1	0.76	heads	1	0.57	heads	1	0.79	heads	1	0.35	tails	0
0.28	tails	0	0.35	tails	0	0.16	tails	0	0.76	heads	1	0.42	tails	0
0.79	heads	1	0.25	tails	0	0.58	heads	1	0.10	tails	0	0.57	heads	1
0.11	tails	0	0.93	heads	1	0.95	heads	1	0.55	heads	1	0.12	tails	0
0.77	heads	1	0.19	tails	0	0.40	tails	0	0.60	heads	1	0.05	tails	0
0.46	tails	0	0.84	heads	1	0.43	tails	0	0.35	tails	0	0.82	heads	1
0.25	tails	0	0.02	tails	0	0.47	tails	0	0.81	heads	1	0.78	heads	1
0.99	heads	1	0.26	tails	0	0.22	tails	0	0.18	tails	0	0.71	heads	1
0.64	heads	1	0.67	heads	1	0.22	tails	0	0.46	tails	0	0.36	tails	0
0.11	tails	0	0.77	heads	1	0.97	heads	1	0.66	heads	1	0.26	tails	0
0.11	tails	0	0.60	heads	1	0.60	heads	1	0.02	tails	0	0.29	tails	0
0.71	heads	1	0.66	heads	1	0.62	heads	1	0.39	tails	0	0.74	heads	1
0.07	tails	0	0.77	heads	1	0.38	tails	0	0.32	tails	0	0.57	heads	1
0.71	heads	1	0.23	tails	0	0.94	heads	1	0.43	tails	0	0.80	heads	1
0.68	heads	1	0.86	heads	1	0.32	tails	0	0.22	tails	0	0.24	tails	0
0.45	tails	0	0.51	heads	1	0.79	heads	1	0.72	heads	1	0.06	tails	0
0.01	tails	0	0.66	heads	1	0.79	heads	1	0.60	heads	1	0.10	tails	0
0.48	tails	0	0.19	tails	0	0.02	tails	0	0.97	heads	1	0.98	heads	1
0.17	tails	0	0.74	heads	1	0.47	tails	0	0.50	tails	0	0.77	heads	1
0.05	tails	0	0.65	heads	1	0.52	heads	1	0.94	heads	1	0.29	tails	0
0.29	tails	0	0.08	tails	0	0.08	tails	0	0.29	tails	0	0.97	heads	1
0.83	heads	1	0.79	heads	1	0.33	tails	0	0.40	tails	0	0.05	tails	0
0.88	heads	1	0.69	heads	1	0.75	heads	1	0.21	tails	0	0.40	tails	0
0.22	tails	0	0.29	tails	0	0.10	tails	0	0.13	tails	0	0.46	tails	0
0.85	heads	1	0.24	tails	0	0.36	tails	0	0.35	tails	0	0.94	heads	1
0.45	tails	0	0.60	heads	1	0.38	tails	0	0.26	tails	0	0.10	tails	0
0.78	heads	1	0.48	tails	0	0.76	heads	1	0.65	heads	1	0.21	tails	0
0.18	tails	0	0.08	tails	0	0.58	heads	1	0.62	heads	1	0.32	tails	0
0.86	heads	1	0.16	tails	0	0.76	heads	1	0.45	tails	0	0.61	heads	1
0.76	heads	1	0.72	heads	1	0.91	heads	1	0.78	heads	1	0.42	tails	0
0.35	tails	0	0.29	tails	0	0.48	tails	0	0.73	heads	1	0.26	tails	0
														
250	total	46			49			51			52			52

[RaulVB]

56. So it wasn't "God's intervention"?

Are you sure?

Thanks, TIA.

[Roger_Otip]

2. this can't be right

is it only 600 out of 1000? if it is then that's just over half, so i would expect it to be quite likely.

[Live Free Or Diebold]

19. No, that's quite right.

If you had a fair coin and flipped it 1,000 times, you'd expect about 500 flips to be "heads". You wouldn't be too fazed if the actual count of heads was 501 or 496 or even 510, but off by 100 would truly be a freak occurance. In a random distribution, standard deviation decreases with sample size - and 1,000 flips is a pretty good sized sample.

If you checked all of the errors, and they showed 600 errors in Bush's favor and 400 against, you could feel very confident that the direction of the errors (for or against Bush) do not occur with equal (or even nearly equal) probability. There must be some other explanation for the bias. It might be a quite innocent reason (say, simply that errors favoring Kerry were not reported in your sample), or it might not be innocent, but there's definitely a skew in the data in that scenario.

[breadbox]

47. actually, standard deviation increases

but the relative width of the distribution gets smaller (compared
to the sample size)

More precisely, in a random distribution standard deviation
(which measures the width of the bulk of the distribution) grows
like the square root of the sample size: for N=1000, the standard
deviation is the square root of 250, which is about 16. Hence
a deviation of one hundred from the mean is more than six standard
deviations away from the mean.

You'll often hear six sigma mentioned in big business: this refers,
for example, to getting a manufacturing process to be so accurate that
random deviations would have to be more than 6 standard deviations away
from the mean for something bad to happen --- the point being that
this is a tremendously unlikely event: odd are about 1/10^9.

[newyawker99]

59. Hi breadbox!!

Welcome to DU!! :toast:

[TruthIsAll]

21. THIS IS JUST A HYPOTHETICAL. I AM NOT SAYING THE DATA SHOWS THIS.

This is for future reference - when data is compiled.

VIEW THIS THREAD
http://www.democraticunderground.com/discuss/duboard.php?az=view_all&address=203x117058

Yes I assume event independence. It is equivalent to 1000 coin flips.
You would expect close to 500 heads.

[Hamoth]

23. Ohhhh O.k.

Then can we get a journalist on the data end? I think Kieth or somone similar could easily get the lists of machine errors from a given state or group of states.

[TruthIsAll]

55. The Excel BINOMDIST can't go over 617: 1 out of 57.7 TRILLION !

N.....Prob........1 out of
500	0.487        2
550	0.000695	1,437
600	9.005E-11	11,103,727,321
610	1.109E-12	901,531,303,647
611	6.912E-13	1,446,707,236,547
612	4.255E-13	2,349,908,493,280
613	2.573E-13	3,885,763,267,792
614	1.513E-13	6,608,363,356,376
615	8.482E-14	11,789,527,820,342
616	4.318E-14	23,154,753,868,229
617	1.731E-14	57,738,456,761,160
618	0	#DIV/0!

[Hamoth]

3. Where's the excell sheet?

I wanna review and see where the data is from, and how this was run.

In my early attempt to put something like this together, I found that data fit 3 categories: Favoring Republican, Favoring Dem, unknown favor. To characterize what I was seeing, my initial sample showed my Ohio data had 8 errors, 1 favoring Dem and 5 favoring republicans 2 unknown.

[Roger_Otip]

5. then the binomial distribution cannot be used

since that's for when there are only 2 possibilities.

[Hamoth]

6. Yeah, Kinda what I was thinking

But where's the dataset for this round 600 out of 1000 number being floated? Is this a hypothetical tally?

[bemis12]

28. It sounds hypothetical

It's just something he's made up, again. I don't think such a database exists. It's a strawman, that's why he's ignored requests for the database.

edit typo

[TruthIsAll]

33. Hey, Bemis you are barking up the wrong tree.

The database exists. Of the 34 documented cases of FL Touchscreen "gliches" which reversed the votes, 33 went from Kerry to Bush.

And that's just fo starters.
Now why don't you go and look at it.

I guess it must be real uncomfortable for you now, having run out of yarn to spin, just like CNN.

THE TRUTH TRAIN IS COMING FAST AND YOU HAD BETTER HOP ON OR IT WILL RUN RIGHT OVER YOU.

[Hamoth]

35. Where are you getting the data?

Do you have it for places besides florida?
May I have a copy of any databse you have with the subject?
Are these media reports, or official incidents?

[bemis12]

37. No I'm not

That's not at all the database I was discussing. It's the one you fabricated these numbers from for this thread. If there's another, it will have to be discussed separately.

*running in awe from the "Truth Train"*

[Name removed]

39. Deleted message

Message removed by moderator. Click here to review the message board rules.

[TruthIsAll]

22. There ARE two possibilities. The glich favors OR does not favor Bush.

tia

[Hamoth]

24. But with a real dataset,

some might favor a given senator, or third party candidate at the expense of both Kerry and Bush...We really don't know for sure if all errors fall into both categories untill we have a full dataset in front of us.

[MaineYooper]

40. you could use a multinomial distribution instead

but I don't think Excel has it hard coded, so it would have to be manually determined.

[Truman01]

4. That doesn't make any sense. TIA n/t

[TruthIsAll]

29. See post # 27 n/t

.

[MaineYooper]

7. be careful and thorough

Your analysis is solid under the assumption that all of the errors are independent of each other, and that there are no systematic problems or correlations.

I'm not arguing against the conclusions, but you need to be careful on this, as a good statistician will immmediately look at the assumption of independence as tenuous. If fraud is going to be proven, all of the easy explanations (such as correlated errors) need to be negated strongly.

[reality_bites]

8. Note to the master

Grouping every machine error in Ohio together and calling them random, does not make them random.

Case in point: machines that have been tampered with, aren't exhibiting random errors - they are exhibiting intentional localized systemic errors.

Were machines tampered with in Ohio ? If so, your calculations don't mean anything.

By the way, what is a glitch ?

[Hamoth]

9. That's the point

By showing the skew in the data, you prove with a solid fact that the machine "errors" could not have been random.

But I'm still waiting for the excell sheet and an ability to review the dataset if one exists.

[reality_bites]

10. Now you are maing my point.

If the errors aren't random, but skewed, then he can't use the formula he's using. The formula h4e's using only applies to random samples. Therefore calculations based on the formula, again, mean nothing.

[Hamoth]

11. Um...either you are stats-man

or you are missing my meaning...Do you have an alternate formula? Becuase what you seem to be implying is that it is given that the fraud occured. "Knowing that the numbers are skewed..." which we don't, in fact know. In fact, everyone tells me that this is totally random.

The current "official" truth is that the machine errors are random. Right? So what are the odds that these random errors would distribute so lopsided? If they are astronomical, then we know that the numbers are not random, but the act of some kind of planning or design.

But AGAIN, I really want to see whatever data set there is here.

[TruthIsAll]

27. The fact that the results indicate these are NOT random events

(like a coin flip) is exactly the point.

We HYPOTHESIZE that the occurrences are random. So we would expect the Law of Large Numbers to bring about a 50% split (like 1000 coin flips - 500 HEADS and 500 TAILS). In other words, the ACTUAL frequency should converge to the THEORETICAL 50% value if these were truly RANDOM events.

We are attempting to show that a 600-400 split could NOT be due to chance.

The assumption of independence is a fair one, as the machine "gliches" are scattered throughout hundreds of precincts.
We assume the machines are independent of each other.

We do not assume beforehand that the machines have been programmed to display "Bush" when the voter presses "Kerry". We can strongly suspect it, though, if 600 of 1000 do just that.

[Truman01]

43. Ok, now that makes sense to me..... Question:

How do we know that the split was 600/400? How do we know that all or a representative sample of the incidences were reported? By the way, my questions are out of pure ignorance. I appreciate your knowledge in this area.

TC

[Old and In the Way]

12. I'll be quite interested to see the accummulated incidences of

voting problems, by state, by vote system, and by candidate favored. I hope someone is accummulating this data. Based on your postings yesterday, I'd say you are being quite conservative on the 600/400 distribution. That information will provide fertile ground for making the case that Republicans gamed this election.

[Hamoth]

13. There is something like that

http://www.votersunite.org/electionproblems.asp?offset=80&sort=date&selectstate=ALL&selectproblemtype=Machine%20malfunction

Kinda...It's all Media reports on election problems, sorted by date, state, type.

[smarkit]

14. Who is doing the reporting

If the database is the set of newspaper articles etc. on that site I can't remember you have to consider the following:

Is is more likely that errors favoring the loser of the election will be reported? Are people more likely to be searching for errors favoring Kerry than for those favoring Bush?

We have had too many erroneous arguments based on statistics.

[Hamoth]

16. That's why I asked for better data

And keep asking for this thread's author's dataset...

The link I provided is educational in it's way...but not scientific. I need data from counties and official sources to really report on this and do an analysis.

but I'm not sure if the author of the thread has already done that or not...

[Old and In the Way]

18. Let's see the whole universe of incidences.

The "loser" argument doesn't wash because on 11/2 during the polling times no one knew who won....Bush supporters would most certainly have been just as motivated to report problems as Kerry supporters. So far, I've heard no incidence where a voter complaining that Kerry's name pops up when he voted for Bush...have you?

[Hamoth]

20. Yes, I have.

go to votersunite.org, there are machine errors that inflated for Kerry.

Here's one:
http://www.trivalleyherald.com/Stories/0,1413,86~10669~2507743,00.html

There's a handfull more at:
http://www.votersunite.org/electionproblems.asp?offset=80&sort=date&selectstate=ALL&selectproblemtype=Machine%20malfunction

[TruthIsAll]

52. Hey Old, they are really coming out today, aren't they?

tia

[TruthIsAll]

51. Another one. Must be getting very close.

.

[newyawker99]

60. Hi smarkit!!

Welcome to DU!! :toast:

[genieroze]

15. How many errors favored Kerry?

I would say none, but I could be wrong.

[Hamoth]

17. That would be wrong

I've seen a handfull that do.

[hlthe2b]

25. I like seeing the probabilities, but unfortunately, a very large swath of

the public, the media, and even a handful of DUers are not swayed by extreme mathematical probabilities (actually INprobabilities). Remember the response to the DNA results with OJ? Even before the suggestion of contamination was out there, it seemed a large number of people were reacting with the "yeah, but," response.

Science and mathematics seem to be two areas where we are failing in both educating the public and conveying the relevence to the public. I just saw a very heated debate about the term "parasite" in relation to a pre-term human fetus. While I don't think most were condoning using the term because of sensitivities, many were angry when it was pointed out that the scientific definition was quite accurate.

Sorry to get off on a tangent, but this just struck me today. Any thoughts, Truthisall?

[Hamoth]

30. What we need is material

that can justify a news story basically.

I thought the exit poll stats were open to debate by the public, because it's magical stuff to them.

But saying, for example, that 90% of these random errors favored one guy, well that's something people can grasp. It's something the media would tout as well.

I really want to see this study done.

[Old and In the Way]

36. Really important work you're doing TIA.

Assuming systematic programming errors are contributing to these reported errors, I'd have to woner how many went unreported. I suspect there is still a large segment of the population that is thorough intimidated with computers and would not realize or, if they did, wouldn't report the errors.

I really think this is an important avenue of inquiry and your probabilities of the non-randomness of the error results should be a cornerstone for reforming our voting system.

I'm happy to see my state Maine is leading the way on the reform:

http://www.votersunite.org/info/maine-ld1759.asp

On April 22, 2004, Maine's Governor John Elias Baldacci signed LD1759 into law. ""An Act To Ensure the Accurate Counting of Votes" was sponsored by Representative Hannah Pingree. The bill was passed by the Maine House on April 12 and the Senate on April 13. The law states, in part:

Any computer software relating to such voting machines must employ an open-source operating code that is fully accessible to the Office of the Secretary of State and agents of that office.

and

All voting machines in the State must produce a physical ballot, equivalent or superior to that of a hand-cast ballot, that unambiguously reflects the intent of the voter and that each voter shall personally review and deliver to an official ballot box. Touch screen voting machines must produce a legible, large-print ballot for verification by each voter of that voter's electoral choices before it is placed in the official ballot box. Each such ballot must also identify the individual machine that produced it while not identifying the voter.

[TruthIsAll]

34. The lack of math knowledge is from the general dumbing-down

that the Repukes have brought about over the last 25 years.
Hopefully, the analysis will re-awaken the need for eempasis on the subject. This just may become a math learning experience for millions.

In any case, the lawyers and investigators involved will surely analyze the data to make what will surely be a very powerful case for fraud.

And their analyses may be quite similar to mine.

[buddysmellgood]

26. The exit polls alone tell us something is wrong.

The odd that exit polls would be off to the degree that they are in favor of on candidate in three battleground states...It's ridiculous. But I guess it's okay. It's not like we live in Ukraine.

[Amy6627]

31. This is great info!

Thanks for your work on this. By the way has anyone heard anything about Cliff Arnebeck, Counsel in Lawsuit Challenging Presidential Election in Ohio. Did the lawsuite get filed?

[myschkin]

41. don't stop

TIA, maybe you make a story out of it, a study. So this would be very convincing for the media...

Good luck!

[TruthIsAll]

42. I'll leave that to the researchers and lawyers.They know far better than I

what needs to be done to prove the case. It's too bad they don't have the analytical and juicial infrastructure they need to bring charges.

Nothing sticks to Bush. Nothing. Factual pursuit, truth and fairness are useless, out-of-date concepts.

Whatever happened to the Plane investigation?
What about the full 9/11 report? You know, the one they would not release PRIOR to election - because of Bush demands.

WOULD JUST ONE DAMN SENATOR LISTEN TO KRISTEN BREITWEISER AND THE OTHER 9/11 AND IRAQ WIDOWS AND WIDOWERS AND END THIS NIGHTMARE OF LIES?

Freeman, Paulos and Univ. of Berkeley have already proved an overwhelming circumstantial case for fraud. Doing mathematics is the easy part.

I cannot imagine that a professional statistician/researcher who is aware of the facts of this election could truly believe that it was NOT stolen, yet respectable political polling gurus have triedy to spin the same ridiculous exit poll theories which have been concocted by the Repukes and Mitofsky. It really makes you wonder.

Everyone has his or her price, I guess.

The Age of Reason was in vogue when our nation was founded. We have entered the Age of Treason, where fealty to the fascists is more important than the resuscitation of our moribund democracy.

[Bread and Circus]

44. TIA, where the hell are U getting this 600 out of a 1000 number?

[TruthIsAll]

50. ITS A HYPOTHETICAL EXAMPLE . I ALREADY SAID SO.

THE PURPOSE OF THIS THREAD WAS TO ANTICIPATE THE NEED FOR CALCULATING PROBABILTIES OF FRAUD RELATED TO CASES OF MACHINE "GLICHES" WHEN THEY ARE COMPILED.

I HAVE NOT DONE SO. HOWEVER, IF YOU LOOK AT OTHER THREADS AND LINKS ON THIS TOPIC, YOU WILL SEE THAT A TREMENDOUS AMOUNT OF RAW DATA HAS BEEN COMPILED AND AVAIALBE FOR ANALYSIS.

FROM WHAT I HAVE ALKREADY SEEN AND POSTED ON IN OTHER THREADS, THE VAST MAJORITY OF MACHINE "GLICHES' IN FlORIDA WORKED IN BUSH'S FAVOR.

SO 600 OUT OF 1000 IS VERY CONSERVATIVE HYPOTHETICAL.

I SUSPECT THAT 80-90% OF MACHINE "GLICHES" HELPED BUSH, IN WHICH CASE THE PROBABILITY OF MASSIVE FRAUD IS MUCH BEYOND THE 1 IN 11 MILLION SHOWN IN THIS HYPOTHETICAL MATHEMATICAL EXAMPLE.

NOTICE, I SAID HYPOTHETICAL AGAIN.

[briemann]

45. This is a good analysis. but

there is a flaw. A binomial distribution is obtained as the sum of independent bernoulli trials with an equal probability of "success". In this case, your value of .5 is the probability of success. The flaw (actually two flaws) are:

1. If any discrepancies happened on the same machine, one cannot assume independence.
2. Similarly, as the probability of discrepancies probably varied between machines, one cannot assume equal probabilities of success.

So, the actual model is more complex than a simple binomial.

[breadbox]

48. to put it as TIA intended, I think

What this shows is that the hypothesis that the machine errors are
unbiased between candidates is unlikely (extremely) to be true.
Then the question becomes "what is the source of the bias?"

The model is quite general enough for the purposes here: there are
a number of errors of the type "favors bush" or "favors kerry" which
occur. The probability that an error favors bush is p_b, and that
it favors kerry is 1-p_b. Now we can test the hypothesis that
p_b=p_k=1/2. We end up concluding definitively that this is not the
case. It doesn't say anything about what caused the bias, but it does
show that is is there. It could be machines, it could be demos report
bias and repubs just suck it up: but the results are biased.

[jwmealy]

54. Yo, Briemann! What do you make of this?

Hi, Briemann.

I'm a newbie so I can't start a thread. So this is only tangential to TIA's thread. He and I have conversed before.

I formed a master hypothesis for testing: The improbably large red shift effect stems from the presence of underlying largescale election tampering in Nov. 2004 presidential election. I developed a set of test hypotheses on the basis of it:

Hypothesis 1: The red shift (discrepancy between best late-in-the-day exit poll figures and tabulated results) will be markedly greater in battleground states. Why? Because 1. no need to intervene if the state is already guaranteed for Bush; 2. no point in intervening if the state is expected to go heavy for Kerry, since the amount of intervention will make the discrepancy stick out like a sore thumb. Exposure to risk will increase in proportion to the level of intervention.

Result of Hypothesis 1: Confirmed. The 11 Battleground states show 1.45 times the average of the safe states.

Hypothesis 2: Among the battleground states that show red shift, those states with the most electoral college votes will show the greatest evidence of intervention.

Result of Hypothesis 2: Confirmed. The 5 battleground states with the highest red shift command 1.91 times as many electoral college votes as the bottom 5. (Minnesota has no red shift, and has been dropped from the study because it doesn't show any evidence of electronic tampering.)

Hypothesis 3: Battleground states that have high electoral college votes but relatively low red shift will have been won by Kerry with relatively wide spreads. If Bush were winning strongly, no intervention at all would be required. But if Kerry were winning strongly, someone, in these cases, or some piece of software code, will have decided to pull the plug when it was realized that the software couldn't keep pouring votes in to the point of winning without leaving a conspicuous trail (i.e. a huge red shift).

Result of Hypothesis 3: Confirmed. Michigan is the single state of the 10 that displays this characteristic. With 17 ec votes, it has well above the average (10 ec votes) for the battleground states, and had only 1.30 red shift--far below the average for the 10 states (2.68). Kerry won that state with a 3.4 margin (well above the 2.77 average spread for the 10 states). If we assume, hypothetically, that the exit poll for MI reflects the actual votes cast, then the total intervention that would have been required in order to create a final 1% lead for Bush would be 5.7 (i.e. 1.3 + 3.4 + 1), higher than the highest currently recorded value among the 51 states--including WDC: Vermont, with 5.6. Looks like someone decided to bail out early because it was looking like a lost cause, and/or a software program made the decision based on pre-set parameters.

Hypothesis 4: Battleground states that have low electoral college votes but relatively high red shift will have been won by either candidate, but with a relatively small spread. Someone, or some piece of software, in these cases, will periodically have poured votes in over the day, trying to keep Bush 1% up, but will have given up when some pre-set parameter was reached.

Hypothesis 4: Confirmed. New Hampshire is the single state that meets these criteria. With only 4 ec votes, it has a relatively thin spread of 1.3 points, along with the highest red shift of the 10 states: 4.9, nearly twice the 10-state average. Notice that if you add the Kerry margin for New Hampshire (4.9), plus 1.3 points (the spread), plus 1 point, you get 6.2 red shift required to shift the state to Bush with a 1% margin. Once again, that's greater than the highest red shift number for the 51 states, and presumably beyond some agreed or set maximum parameter, so the plug was pulled.

Hypothesis 5: Every redshifted battleground state that goes for Kerry will show the pattern, (red shift + spread + 1) > 5.6 (the greatest recorded red shift value for the 51 states, recorded in Vermont). That is, in order to put Bush in the lead for that state by 1%, that state's red shift would have to exceed any recorded red shift in the election.

Hypothesis 5: Confirmed. According to this formula, Minnesota would require a red shift of 7.6, Michigan would require 5.7, Pennsylvania would require 6.4, and New Hampshire would require 7.2.

Hypothesis 6: There will be a general correlation in the battleground states between the amount of red shift, on the one hand, and the slenderness of the final point spread on the other hand. Where Bush was winning strongly (heading for a wide spread), little or no intervention will have been needed, and where Kerry was winning strongly (heading for a wide spread), a person or a software setting will have given up pumping in votes early on. Therefore the close races (in the tabulated results) will tend to show the most red shift, because they will have required the most intervention in order to keep Bush slightly ahead.

Hypothesis 6: Confirmed. Average Bush Red Shift + Kerry Neg Blue Shift of the Five Battleground States with the Slimmest Spread was 5.72; Average Red Shift of the Five Battleground States with the Widest Spread was 3.86, a differential of 1.48 to 1.

All things considered, my results seem well correlated with the hypothesis that someone ordered systematic vote-rigging intervention in the battlground states, and succeeded in plugging in to most or all of them except Minnesota.

What do you think of this sort of study? It's kind of a broad brush approach, but every time I form a hypothesis it is confirmed, and/or the appearance of an anomaly within the results of a hypothesis suggests another hypothesis which is confirmed.

For my basic study, with hypotheses 1 and 2 only, see
www.selftest.net/redshift.htm

Webb Mealy

[briemann]

57. If the analysis is correct, then

the statistics are indicative of a pattern. You must also show that the "reverse pattern", ie, blue-shift, is not as commonly seen.

Remember, statistics prove nothing, nor do they identify causality. Prior to losing my job, I built statistical underpinnings to anecdotal cases for government and industry.

[jwmealy]

58. My understanding from TIA's analysis is that the Blue Shifts were

. . .all within the margin of error. . .
whereas the five most red-shifted battleground states were ALL outside the margin of error.

This pattern absolutely demands an explanation. My money (although no one on this list seems to be betting on my side) is on the guess that some kind of intentional social engineering lies behind a certain amount of the red shift phenomenon outside the battleground states, and that the master intention is to obscure an intentional intervention.

[Digit]

46. * is not legit...he wasn't in 2000 and sure as hell is not now

It is BEYOND random chance and STINKS.

[dawn_fayhe]

49. But still

Still, those figures are increadible. Thanks for sharing!

-

Fight the neo-cons!

[LiberalAndProud]

53. Even the preachers know that * was never elected.

He was appointed by the satan gawd they worship (with a little bit of help from his demon spawn)