Z-Score
A Z-score, also known as a standard score, is a statistical measure that quantifies how many standard deviations a data point is from the mean of a dataset. It is used to standardize data, allowing for comparison across different datasets or distributions. This normalization helps in identifying outliers and understanding the relative position of values within a distribution.
Developers should learn Z-scores when working with data analysis, machine learning, or statistical applications, as they are essential for data preprocessing, feature scaling, and anomaly detection. For example, in machine learning, Z-scores are used to normalize features to improve model performance, and in data science, they help detect outliers in datasets like financial transactions or sensor readings.