Accuracy

{
  "id": "MLC-T-ENV-000244",
  "term": "Accuracy",
  "field": "Environment",
  "definition": "1. Closeness of a measured or computed value to its \"true\" value, where the \"true\" value is obtained with perfect information. Due to the natural heterogeneity and stochasticity of many environmental systems, this \"true\" value exists as a distribution rather than a discrete value. In these cases, the \"true\" value will be a function of spatial and temporal aggregation.\n\n2. The degree to which a measurement reflects the true quantitative value of a variable.\n\n3. How closely an instrument measures the true or actual value of the process variable being measured or sensed.\n\n4. The degree of agreement of a measurement (X) with an accepted reference or true value (T); usually expressed as the difference between the two values (X - T), or the difference as a percentage of the reference or true value (100[X - T]/T), and sometimes expressed as a ratio (X/T).\n\n5. A measure of the overall agreement of a measurement to a known value. Accuracy includes a combination of random error (precision) and systematic error (bias) components that are due to sampling and analytical operations; EPA recommends using the terms \"precision\" and \"bias,\" rather than \"accuracy,\" to convey the information usually associated with accuracy.\n\n6. Refers to closeness of a measurement to the true value.\n\n7. The degree to which a calculation, a measurement, or set of measurements agree with a true value or an accepted reference value. \"Accuracy includes a combination of random error (precision) and systematic error (bias) components which are due to sampling and analytical operations; a data quality indicator. EPA recommends that this term not be used and that precision and bias be used to convey the information usually associated with accuracy (QAMS 1993, 1).\"\n\n8. The measure of the correctness of data, as given by the difference between the measured value and the true or standard value.\n\n9. The degree to which a measurement (e.g., the mean estimate of a treatment effect) is true or correct. An estimate can be accurate, yet not be precise, if it is based upon an unbiased method that provides observations having great variation (i.e., not close in magnitude to each other).\n\n10. The degree of agreement between an observed value and an accepted reference value. Accuracy includes a combination of random error (precision) and systematic error (bias) components, which are due to sampling and analytical operations; a data quality indicator. {ORD} {OW/EAD} {OPP} {OW/TSC} {OAR/OAQPS} {OECA} {ORCR}\n\n11. The measure of the correctness of data, as given by the difference between the measured value and the true or standard value. (EPA 1997a, EPA 2004)\n\n12. The degree of agreement between an observed value and an accepted reference value. Accuracy includes a combination of random error (precision) and systematic error (bias) components, which are due to sampling and analytical operations; a data quality indicator.\n\n13. Degree of agreement between average predictions of a model or the average of measurements and the true value of the quantity being predicted or measured. (FAO/WHO 2003b)\n\n14. The degree to which a measurement (e.g., the mean estimate of a treatment effect) is true or correct. An estimate can be accurate, yet not be precise, if it is based upon an unbiased method that provides observations having great variation (i.e., not close in magnitude to each other). (NLM/NICHRS 2004)\n\n15. Absolute difference between a reference quantity and the arithmetic mean of ten mean measurements of that quantity. Determine instrument accuracy, repeatability, and noise from the same data set. We specify a procedure for determining accuracy in § 1065.305.\n\n16. Difference between a measurement and true value.[40 CFR 86.1803-01 (CFR 2018)]\n\n17. The degree of agreement between an observed value and an accepted reference value. Accuracy includes random error (precision) and systematic error (bias or recovery) that are caused by sampling and analysis. A data quality indicator. [EPA/600/Z-92/001; EPA 815-B-04-001]\n\n18. Degree to which a calculation, a measurement, or set of measurements agree with a true value or an accepted reference value. \"Accuracy includes a combination of random error (precision) and systematic error (bias) components which are due to sampling and analytical operations; a data quality indicator. EPA recommends that this term not be used and that precision and bias be used to convey the information usually associated with accuracy (QAMS 1993, 1).\"\n\n19. The degree of agreement between an observed value and an accepted reference value. Accuracy includes random error (precision) and systematic error (bias or recovery) that are caused by sampling and analysis. A data quality indicator.",
  "subject": "Science and research",
  "references": [
    "Modeling Glossary",
    "Waste and Cleanup Risk Assessment Glossary",
    "Drinking Water Technical & Legal Terms",
    "Radon Glossary of Terms",
    "Guidance for Quality Assurance Project Plans",
    "Environmental Geophysics Glossary",
    "Environmental Modeling and Assessment Program (EMAP) Master Glossary",
    "EPA 1997a, EPA 2004",
    "NLM/NICHRS 2004",
    "Forum on Environmental Measurements (FEM) Glossary",
    "Thesaurus of Terms Used in Microbial Risk Assessment",
    "40 CFR 1065.1001 (CFR 2013)",
    "40 CFR 86.082-2 (CFR 2018)",
    "Environmental Sampling and Analytical Methods (ESAM) Program Glossary",
    "EMAP Master Glossary",
    "EPA/600/Z-92/001; EPA 815-B-04-001"
  ],
  "url": "https://mlchart.com/terminology/environment/accuracy/"
}