Z-score Calculation: The code calculates the Z-score for each data point in a given dataset, enabling the identification of outliers based on user-defined thresholds. Data Cleaning: Before calculating ...

In this article, we discussed two methods by which we can detect the presence of outliers and remove them. We first detected them using the upper limit and lower limit using 3 standard deviations. We ...

The code demonstrates how outliers can be detected and removed using Z-score, Percentile, and IQR. It focuses on applying these methods to identify and eliminate outliers in climate change data. The ...

Univariate outlier detection involves identifying anomalies in a single variable using statistical measures such as Z-scores and the Interquartile Range (IQR).

Outlier Detection. The z-score is used to identify outliers in a dataset. Any data point with a z-score greater than 3 or less than -3 is considered an outlier.

The reliability and accuracy of thermophysical property data are of central importance for the development of models that describe these properties. In this work, we compare different autonomous ...