This is a simple method for outlier detection, the procedure basically is a Quantile of weibull distribution of the chi square test in python. - statistics outlierdetectionmethods
We may have some small series of data like stock, rolled product thickness, etcetera; sometimes the data is collected manually and we need to detect outliers as a first filter to detect human errors in the collected data and correct them before analysis, in other cases, the data must need be broken down by season, process, etc.
The first question is why each part of this process? The proposed approach to this problem is simply to find an observation error, and for that the problem is built on a calculation ofChi Square test: It can be used to test if the variance of a population is equal to a specified value.Quantile function: probability distribution of a random variable.
2. Measurement’s Accuracy calculation, the classical procedure exposed in the Kalman filter substract the median to the value; i divide the value between the median to make a normalized non-dimentional measure:
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