This module focus on learning the 4 common data classification methods: Quantile, Equal Interval, Standard Deviation, and Natural Breaks. By using one dataset but 4 different classification method, the dataset can be visualized differently. Below is how I interpreted the 4 classification methods. Equal Interval divides a range of data values into equal-sized intervals (based on how many classes are given). It is excellent for uniform distributed data where values are spread out evenly. Extreme values are placed in the lowest or highest class. This can hide some values if some are not evenly distributed. Quantile classifications divide a dataset into classes with the same number of data points, regardless of actual values in those data points. This ensures each class has the same number of data points, which can be beneficial for data that is evenly distributed. ...
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