Audit Selection Report for Thompson School District R2-J Director District B (4 Years)

Proportion of the total number of votes for this contest that were cast within this county: 0.4%

See additional statistical information below...

The audit units are reported for selection in priority order, based on the thresholds below, and the "Sum of Square Roots" pseudorandom number generator using the random seed value 569985350872703 combined with the Batch sequence numbers.

Select the top 0 audit units.

Batch Seq Threshold Random Priority Type Batches Ballots Contest Ballots Dennis L. Breitbarth Over Under
Totals 31 0 37
000025 0.011421 0.025277 0.451842 AB p025_mb_562 150 1 0 0 1
000272 0.011421 0.033268 0.343311 AB p272_mb_698 150 1 1 0 0
000114 0.022712 0.093261 0.243535 AB p114_mb_695 150 2 1 0 1
000277 0.033874 0.195097 0.173627 AB p277_mb_653 150 3 2 0 1
000162 0.011421 0.079993 0.142779 AB p162_mb_655 150 1 0 0 1
000275 0.011421 0.092784 0.123096 AB p275_mb_519 150 1 0 0 1
000042 0.011421 0.112267 0.101733 AB p042_mb_631 150 1 0 0 1
000244 0.011421 0.114911 0.099393 AB p244_mb_543 150 1 0 0 1
000169 0.011421 0.131133 0.087097 AB p169_mb_642 150 1 1 0 0
000179 0.011421 0.141037 0.080981 AB p179_mb_540 150 1 1 0 0
000105 0.022712 0.314941 0.072116 AB p105_mb_536 150 2 0 0 2
000113 0.011421 0.167596 0.068148 AB p113_mb_694 150 1 0 0 1
000092 0.011421 0.171830 0.066469 AB p092_mb_527 150 1 0 0 1
000027 0.011421 0.204039 0.055976 AB p027_mb_532 150 1 1 0 0
000064 0.011421 0.211245 0.054067 AB p064_mb_686 150 1 0 0 1
000066 0.011421 0.218066 0.052376 AB p066_mb_691 150 1 1 0 0
000069 0.033874 0.648126 0.052265 AB p069_mb_341 150 3 1 0 2
000282 0.022712 0.469012 0.048426 AB p282_mb_488 150 2 1 0 1
000018 0.022712 0.527893 0.043024 AB p018_mb_530 150 2 2 0 0
000082 0.011421 0.291195 0.039222 AB p082_mb_535 150 1 0 0 1
000223 0.022712 0.596394 0.038083 AB p223_mb_356 150 2 0 0 2
000009 0.011421 0.317568 0.035965 AB p009_mb_571 150 1 1 0 0
000346 0.033874 0.951514 0.035600 AB p346_mb_382 150 3 1 0 2
000050 0.011421 0.326694 0.034960 AB p050_mb_579 150 1 0 0 1
000126 0.011421 0.383868 0.029753 AB p126_mb_318 150 1 0 0 1
000088 0.022712 0.768779 0.029543 AB p088_mb_506 150 2 1 0 1
000010 0.022712 0.774266 0.029334 AB p010_mb_572 150 2 1 0 1
000266 0.011421 0.395883 0.028850 AB p266_mb_634 150 1 0 0 1
000214 0.022712 0.788070 0.028820 AB p214_mb_305 150 2 0 0 2
000023 0.011421 0.418577 0.027286 AB p023_mb_564 150 1 1 0 0
000383 0.022712 0.870264 0.026098 AB p383_mb_253 150 2 0 0 2
000185 0.011421 0.461370 0.024755 AB p185_mb_689 150 1 1 0 0
000048 0.011421 0.480489 0.023770 AB p048_mb_546 150 1 0 0 1
000186 0.011421 0.488840 0.023364 AB p186_mb_696 150 1 0 0 1
000036 0.011421 0.490256 0.023297 AB p036_mb_557 150 1 1 0 0
000176 0.011421 0.507949 0.022485 AB p176_mb_637 150 1 0 0 1
000033 0.011421 0.552539 0.020671 AB p033_mb_554 150 1 1 0 0
000083 0.011421 0.622839 0.018338 AB p083_mb_521 150 1 1 0 0
000112 0.011421 0.684901 0.016676 AB p112_mb_693 150 1 1 0 0
000074 0.011421 0.685019 0.016673 AB p074_mb_335 150 1 0 0 1
000057 0.011421 0.705503 0.016189 AB p057_mb_662 150 1 1 0 0
000108 0.011421 0.729251 0.015662 AB p108_mb_514 150 1 0 0 1
000203 0.011421 0.732381 0.015595 AB p203_mb_313 131 1 1 0 0
000389 0.011421 0.754972 0.015128 AB p389_mb_428 150 1 0 0 1
000262 0.011421 0.774803 0.014741 AB p262_mb_664 150 1 1 0 0
000173 0.011421 0.815687 0.014002 AB p173_mb_645 150 1 0 0 1
000081 0.011421 0.854479 0.013366 AB p081_mb_470 150 1 1 0 0
000072 0.011421 0.855452 0.013351 AB p072_mb_338 74 1 1 0 0
000213 0.011421 0.862405 0.013244 AB p213_mb_376 150 1 1 0 0
000075 0.011421 0.914968 0.012483 AB p075_mb_334 118 1 1 0 0
000148 0.011421 0.963496 0.011854 AB p148_mb_463 150 1 0 0 1
000059 0.011421 0.971916 0.011751 AB p059_mb_699 150 1 1 0 0
000320 0.011421 0.996435 0.011462 AB p320_mb_395 150 1 1 0 0

Audit statistics

The "Number of audit units to audit" is based on the NEGEXP method, which is very efficient and requires selecting larger audit units with higher probability than smaller ones. The numbers given here are based on a confidence level of 75%. I.e. they are designed so the audit will either 1) find a discrepancy and call for an escalation or full hand recount, or 2) reduce the risk of confirming an incorrect outcome to (100 - 75)%, even if the tally system has been manipulated. A maximum "within-precinct-miscount" of 20% is assumed. See On Auditing Elections When Precincts Have Different Sizes, by Javed A. Aslam, Raluca A. Popa and Ronald L. Rivest


Contest: Thompson School District R2-J Director District B (4 Years)

Number of precincts: 53
Total number of votes cast:  68
Average number of votes/precinct: 1.28301886792
Median number of votes/precinct: 1
Maximum number of votes/precinct: 3
Minimum number of votes/precinct: 1
Ratio of max/min: 3.0
margin =  70.99 percent, 48.2732 votes
s =  0.2  (maximum within-precinct-miscount)
alpha =  0.25  (confidence is 1 - alpha:  0.75 )

Rule of Thumb says:
    0.781120924705 precincts.
    expected workload =  2.56603773585 votes counted.

APR says:
    b = 94.06175 precincts needed to hold corruption
    u =  1 precincts to audit
    expected workload =  1.28301886792 votes
    confidence level to find one of b =  1.77475
    bmin = 53
    confidence level to find one of bmin =  1.0

SAFE says:
    bmin = 53
    Number of precincts to audit = u = 1
    Confidence level achieved =  1.0
    expected workload =  1.28301886792

Negexp says:
    w = 34.8217531239
    largest probability =  0.0338741920402
    smallest probability =  0.0114213479072
    expected number of precincts audited =  0.774308077953
    expected workload =  1.18196346783 votes counted

PPEBWR says:
    t =  1
    largest total probability =  0.0441176470588
    smallest total probability =  0.0147058823529
    expected number of precincts audited = 1.0
    expected workload =  1.52941176471 votes counted.
    max difference from negexp =  0.0102434550186