Audit Selection Report for Thompson School District R2-J Director District F (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 Leonard E. Sherman Over Under
Totals 33 0 35
000025 0.011354 0.025277 0.449181 AB p025_mb_562 150 1 0 0 1
000272 0.011354 0.033268 0.341289 AB p272_mb_698 150 1 1 0 0
000114 0.022579 0.093261 0.242109 AB p114_mb_695 150 2 1 0 1
000277 0.033677 0.195097 0.172616 AB p277_mb_653 150 3 2 0 1
000162 0.011354 0.079993 0.141938 AB p162_mb_655 150 1 0 0 1
000275 0.011354 0.092784 0.122371 AB p275_mb_519 150 1 0 0 1
000042 0.011354 0.112267 0.101134 AB p042_mb_631 150 1 1 0 0
000244 0.011354 0.114911 0.098808 AB p244_mb_543 150 1 0 0 1
000169 0.011354 0.131133 0.086584 AB p169_mb_642 150 1 1 0 0
000179 0.011354 0.141037 0.080504 AB p179_mb_540 150 1 1 0 0
000105 0.022579 0.314941 0.071694 AB p105_mb_536 150 2 0 0 2
000113 0.011354 0.167596 0.067747 AB p113_mb_694 150 1 0 0 1
000092 0.011354 0.171830 0.066077 AB p092_mb_527 150 1 0 0 1
000027 0.011354 0.204039 0.055646 AB p027_mb_532 150 1 1 0 0
000064 0.011354 0.211245 0.053749 AB p064_mb_686 150 1 0 0 1
000066 0.011354 0.218066 0.052067 AB p066_mb_691 150 1 1 0 0
000069 0.033677 0.648126 0.051961 AB p069_mb_341 150 3 1 0 2
000282 0.022579 0.469012 0.048142 AB p282_mb_488 150 2 0 0 2
000018 0.022579 0.527893 0.042772 AB p018_mb_530 150 2 2 0 0
000082 0.011354 0.291195 0.038991 AB p082_mb_535 150 1 0 0 1
000223 0.022579 0.596394 0.037860 AB p223_mb_356 150 2 0 0 2
000009 0.011354 0.317568 0.035753 AB p009_mb_571 150 1 1 0 0
000346 0.033677 0.951514 0.035393 AB p346_mb_382 150 3 1 0 2
000050 0.011354 0.326694 0.034754 AB p050_mb_579 150 1 0 0 1
000126 0.011354 0.383868 0.029578 AB p126_mb_318 150 1 0 0 1
000088 0.022579 0.768779 0.029370 AB p088_mb_506 150 2 1 0 1
000010 0.022579 0.774266 0.029162 AB p010_mb_572 150 2 1 0 1
000266 0.011354 0.395883 0.028680 AB p266_mb_634 150 1 0 0 1
000214 0.022579 0.788070 0.028651 AB p214_mb_305 150 2 1 0 1
000023 0.011354 0.418577 0.027125 AB p023_mb_564 150 1 1 0 0
000383 0.022579 0.870264 0.025945 AB p383_mb_253 150 2 0 0 2
000185 0.011354 0.461370 0.024609 AB p185_mb_689 150 1 1 0 0
000048 0.011354 0.480489 0.023630 AB p048_mb_546 150 1 0 0 1
000186 0.011354 0.488840 0.023227 AB p186_mb_696 150 1 1 0 0
000036 0.011354 0.490256 0.023160 AB p036_mb_557 150 1 1 0 0
000176 0.011354 0.507949 0.022353 AB p176_mb_637 150 1 0 0 1
000033 0.011354 0.552539 0.020549 AB p033_mb_554 150 1 1 0 0
000083 0.011354 0.622839 0.018230 AB p083_mb_521 150 1 1 0 0
000112 0.011354 0.684901 0.016578 AB p112_mb_693 150 1 1 0 0
000074 0.011354 0.685019 0.016575 AB p074_mb_335 150 1 0 0 1
000057 0.011354 0.705503 0.016094 AB p057_mb_662 150 1 1 0 0
000108 0.011354 0.729251 0.015570 AB p108_mb_514 150 1 0 0 1
000203 0.011354 0.732381 0.015503 AB p203_mb_313 131 1 1 0 0
000389 0.011354 0.754972 0.015039 AB p389_mb_428 150 1 0 0 1
000262 0.011354 0.774803 0.014654 AB p262_mb_664 150 1 1 0 0
000173 0.011354 0.815687 0.013920 AB p173_mb_645 150 1 0 0 1
000081 0.011354 0.854479 0.013288 AB p081_mb_470 150 1 1 0 0
000072 0.011354 0.855452 0.013273 AB p072_mb_338 74 1 1 0 0
000213 0.011354 0.862405 0.013166 AB p213_mb_376 150 1 1 0 0
000075 0.011354 0.914968 0.012409 AB p075_mb_334 118 1 1 0 0
000148 0.011354 0.963496 0.011784 AB p148_mb_463 150 1 0 0 1
000059 0.011354 0.971916 0.011682 AB p059_mb_699 150 1 1 0 0
000320 0.011354 0.996435 0.011395 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 F (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 =  71.413 percent, 48.56084 votes
s =  0.2  (maximum within-precinct-miscount)
alpha =  0.25  (confidence is 1 - alpha:  0.75 )

Rule of Thumb says:
    0.776494117945 precincts.
    expected workload =  2.56603773585 votes counted.

APR says:
    b = 94.622225 precincts needed to hold corruption
    u =  1 precincts to audit
    expected workload =  1.28301886792 votes
    confidence level to find one of b =  1.785325
    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 = 35.0292415247
    largest probability =  0.0336769626134
    smallest probability =  0.011354081466
    expected number of precincts audited =  0.769761457839
    expected workload =  1.17503646341 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 =  0.0104406844454