Identifying and Eliminating Gross Errors Using the 3-Sigma Rule
Implementation of the 3-sigma rule for detecting and removing gross errors through MATLAB programming, including statistical calculations and outlier filtering algorithms.
Measurement Error Processing Algorithms
This system provides a human-machine interface for test data input, intermediate calculation results, and selection criteria for gross error discrimination. Code implementation typically involves data validation modules, statistical processing functions, and error detection algorithms. 1. Systematic Errors Errors that maintain constant magnitude and sign under identical conditions, or change according to specific patterns when conditions alter. Examples include inaccuracies in standard values or instrument calibration. Systematic errors can be classified as: (1) Based on error determination level: - Determined systematic errors: Known magnitude and sign - Undetermined systematic errors: Uncertain magnitude/sign but estimable range (2) Based on error patterns: - Constant systematic errors: Fixed magnitude and sign
MATLAB Implementation for Eliminating Gross Errors Using Grubbs' Test
MATLAB code implementation for identifying and removing gross errors in data analysis using Grubbs' outlier detection method, with enhanced technical descriptions of the algorithm and implementation approach.