38609597
Description
Flashcards by Matt Evans, updated more than 1 year ago
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Created by Matt Evans
almost 2 years ago
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| Question | Answer |
| Benford’s law | The principle that in any large, randomly produced set of natural numbers, there is an expected distribution of the first, or leading, digit with 1 being the most common, 2 the next most, and down successively to the number 9. |
| computer-assisted audit techniques (CAATs) | Automated scripts that can be used to validate data, test controls, and enable substantive testing of transaction details or account balances and generate supporting evidence for the audit. |
| descriptive analytics | Procedures that summarize existing data to determine what has happened in the past. Some examples include summary statistics (e.g., Count, Min, Max, Average, Median), distributions, and proportions. |
| diagnostic analytics | Procedures that explore the current data to determine why something has happened the way it has, typically comparing the data to a benchmark. As an example, these allow users to drill down in the data and see how they compare to a budget, a competitor, or trend. |
| fuzzy matching | Process that finds matches that may be less than 100 percent matching by finding correspondences between portions of the text or other entries. |
| predictive analytics | Procedures used to generate a model that can be used to determine what is likely to happen in the future. Examples include regression analysis, forecasting, classification, and other predictive modeling. |
| prescriptive analytics | Procedures that work to identify the best possible options given constraints or changing conditions. These typically include developing more advanced machine learning and artificial intelligence models to recommend a course of action, or optimizing, based on constraints and/or changing conditions. |
| process mining | Analysis technique of business processes used to diagnose problems and suggest improvements where greater efficiency may be applied. |
| t-test | A statistical test used to determine if there is a significant difference between the means of two groups, or two datasets. |
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