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Risk-limiting audit

Risk-limiting audit is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Risk-limiting audit rather than just read about it. In short: A risk-limiting audit (RLA) is a post-election tabulation auditing procedure which can limit the risk that the reported outcome in an election contest is incorrect. It generally involves (1) storing voter-verified paper ballots securely until they can be checked, and (2) manually examining a statistical sample of the paper ballots until enough evidence is gathered to meet the risk limit.

Risk-limiting audit — main illustration
Risk-limiting audit — illustration

Key takeaways

  • Risk-limiting audit belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Risk-limiting audit to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Risk-limiting audit from memory before moving on to harder problems.

Reference excerpt

A risk-limiting audit (RLA) is a post-election tabulation auditing procedure which can limit the risk that the reported outcome in an election contest is incorrect. It generally involves (1) storing voter-verified paper ballots securely until they can be checked, and (2) manually examining a statistical sample of the paper ballots until enough evidence is gathered to meet the risk limit. Advantages of an RLA include: samples can be small and inexpensive if the margin of victory is large; there are options for the public to watch and verify each step; and errors found in any step lead to corrective actions, including larger samples, up to a 100% hand count if needed. Disadvantages include: the sample needs to be a large fraction of all ballots to minimize the chance of missing mistakes, if any contest is close; and it is hard to check computer totals publicly, except by releasing computer records to the public. If examining sampled ballots shows flaws in ballot storage, the usual approach cannot recover correct results, and researchers recommend a re-vote if the number of ballots held in flawed storage is enough to change winners. An alternative to re-votes is to create and verify backups of the paper ballots soon after they are voted, so there is an alternative to flawed storage of the original ballots. As with other election audits, the goal is to identify not only intentional alterations of ballots and tallies, but also bugs in election machines, such as software errors, scanners with blocked sensors or scanners skipping some ballots. The approach does not assume that all ballots, contests or machines were handled the same way, in which case spot checks could suffice. The sample sizes are designed to have a high chance of catching even a brief period when a scratch or fleck of paper blocks one sensor of one scanner, or a bug or hack switches votes in one precinct or one contest, if these problems affect enough ballots to change the result. Comparisons can be done ballot-by-ballot or precinct-by-precinct, though the latter is more expensive.

Categories of audits

There are three general types of risk-limiting audits. Depending on the circumstances of the election and the auditing method, different numbers of ballots need to be hand-checked. For example, in a jurisdiction with 64,000 ballots tabulated in batches of 500 ballots each, an 8% margin of victory, and allowing no more than 10% of any mistaken outcomes to go undetected, method 1, ballot comparison, on average, needs 80 ballots, method 2, ballot polling, needs 700 ballots, and method 3, batch comparison, needs 13,000 ballots (in 26 batches). The methods are usually used to check computer counts, but methods 2 and 3 can also be used to check accuracy when the original results were hand-counted. The steps in each type of risk-limiting audit are:

Ballot comparison. Election computers provide their interpretation of each ballot ("cast vote record"); humans check computers' cast vote records against stored physical ballots in a random sample of ballots; an independent computer tabulates all cast vote records independently of earlier tabulations to get new totals; humans report any differences in interpretations and total tallies. Ballot polling. Humans count a random sample of ballots; humans report any difference between manual percentage for the sample and computer percentage for the election. Batch comparison. Election results provide total for each batch of ballots (e.g. precinct); in a random sample of batches humans hand-count all ballots; for 100% of batches humans check by manual addition or independent computer if the election's initial summation of batches was correct; humans report any difference between original tallies and audit tallies. All methods require:

Procedure to re-count all paper ballots more accurately if errors are detected. This is usually planned as a 100% manual count, but could involve fixing or replacing erroneous computers, doing a new computer count, and auditing that, until an audit shows no problem. Auditing all types of ballots, including military, absentee, provisional, etc. Clarifying which contests were audited and which were not, or auditing all contests or a large enough random sample of contests so the chance of missing erroneous results is acceptably low. Auditing a large enough random sample of ballots so the chance of missing mistakes is acceptably low. Selecting a random sample after initial results are public, because telling hackers in advance which contests and ballots will be in the sample, lets them freely hack other contests and ballots. Selecting the random sample before results are final, so errors can be fixed. Doing the manual check immediately when the sample is selected; if insiders have altered computer files, they could use any delay to change sampled ballots to match the erroneous computer files, thus hiding the errors. Having enough security on the ballots during transportation and storage, so neither insiders nor outsiders can change them. Having enough independent participants select different digits of the random number seed, so no one can control the seed and hence the random number series which selects the random sample. Having the public see all steps, including the content of ballots and computer records while officials examine them, to know they are counted accurately. The last three items are hard in one-party states, where all participants may be swayed by the ruling party. Hand-checking ballots (method 1) identifies bugs and hacks in how election computers interpret each ballot, so computer processing can be improved for future elections. Hand-counting ballots (methods 2 and 3) bypasses bugs and hacks in computer counts, so it does not identify exactly what mistakes were made. Independently totaling cast vote records (method 1) or batch totals (method 3) identifies bugs and hacks in how election computers calculate totals. Method 2 does not need this independent totaling step, since it has a large enough sample to identify winners directly. Colorado uses method 1 in most counties. Colorado uses no audit method in one county which hand-count ballots in the first place. Risk-limiting audits are a results audit to determine if votes were tabulated accurately, not a process audit, to determine if good procedures were followed.

… excerpt ends here. Continue reading the full article.

Illustrations

Risk-limiting audit: Sample sizes depend on: winning margin, number of ballots voted, confidence level, and type of audit.
Sample sizes depend on: winning margin, number of ballots voted, confidence level, and type of audit.
Risk-limiting audit: Colorado elections in 2017, sample sizes needed for risk-limiting audits
Colorado elections in 2017, sample sizes needed for risk-limiting audits
Risk-limiting audit: When sample sizes are limited by budget, they still have some likelihood of catching errors.
When sample sizes are limited by budget, they still have some likelihood of catching errors.

Worked examples

Example 1 — a first encounter with Risk-limiting audit

Start with the simplest possible case. Write down what Risk-limiting audit claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Risk-limiting audit before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Risk-limiting audit ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Risk-limiting audit

In research
Risk-limiting audit appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Risk-limiting audit in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Risk-limiting audit is common in secondary-school and first-year university syllabi. It links to neighbouring topics Elections, Elections in the United States, Electoral fraud, so understanding it makes those chapters shorter.
In everyday life
Look for Risk-limiting audit outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Risk-limiting audit in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Risk-limiting audit means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Risk-limiting audit out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Risk-limiting audit in simple terms?

A risk-limiting audit (RLA) is a post-election tabulation auditing procedure which can limit the risk that the reported outcome in an election contest is incorrect. It generally involves (1) storing voter-verified paper ballots securely until they can be checked, and (2) manually examining a statis…

Why does Risk-limiting audit matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Risk-limiting audit?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Risk-limiting audit.

Tags

  • Elections
  • Elections in the United States
  • Electoral fraud
  • Statistical methods
  • Types of auditing

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