{"id":66900,"date":"2025-12-23T18:59:19","date_gmt":"2025-12-24T00:59:19","guid":{"rendered":"https:\/\/www.arbin.com\/?p=66900"},"modified":"2026-02-05T18:42:24","modified_gmt":"2026-02-06T00:42:24","slug":"accuracy-and-precision-overview","status":"publish","type":"post","link":"https:\/\/www.arbin.com\/de\/accuracy-and-precision-overview.html","title":{"rendered":"Accuracy and precision: Overview"},"content":{"rendered":"

1. Introduction<\/strong><\/h2>\n

Battery testing is fundamentally a measurement task. Whether evaluating cycle life, coulombic efficiency, voltage response, or degradation mechanisms, the quality of conclusions depends on the quality of the data. Two concepts govern data integrity in any battery test system: accuracy<\/strong> und Pr\u00e4zision<\/strong>. Although often mentioned together, they describe different aspects of measurement performance. In long-duration battery experiments\u2014where small deviations can accumulate over hundreds or thousands of hours\u2014understanding these differences is essential for obtaining reliable results.<\/p>\n

This application note clarifies the meaning of accuracy and precision, explains why both are critical in battery testing, and illustrates practical examples using common test parameters such as voltage, current, and coulombic efficiency. Finally, it highlights how high-quality instrumentation (e.g., Arbin LBT<\/span><\/span><\/span> systems with MITS<\/span><\/span><\/span> software) helps minimize errors and improve data confidence.<\/p>\n

2. What is the difference between accuracy and precision<\/strong><\/h2>\n
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Term<\/p>\n

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Meaning<\/p>\n

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Practical Interpretation<\/p>\n

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Genauigkeit<\/strong><\/p>\n<\/td>\n

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Closeness to the true value<\/p>\n<\/td>\n

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\u201cIs the measurement correct?\u201d<\/p>\n<\/td>\n<\/tr>\n

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Pr\u00e4zision<\/strong><\/p>\n<\/td>\n

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Repeatability and low variation<\/p>\n<\/td>\n

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\u201cIs the measurement consistent?\u201d<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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Accuracy error<\/strong> shifts all measurements up or down, while precision error<\/strong> causes measurements to scatter. A system can be accurate but not precise, precise but not accurate, both, or neither.<\/p>\n