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CFA Level I · CFA Level I Exam · Introduction to Financial Data Science

A dataset contains one feature measured in euros, ranging from 20,000 to 900,000, and another feature measured as a ratio from 0.1 to 2.5. The analyst intends to use a distance-based algorithm and wants both features to have a mean of zero and a standard deviation of one. The analyst should most likely apply:

Standardization is the right choice. It subtracts each feature's mean and divides by its standard deviation, giving a mean of zero and a standard deviation of one. Min-max normalization rescales to a 0 to 1 range, and winsorization only caps extreme values without rescaling.

  1. Anormalization using minimum and maximum values
  2. Bstandardization using the mean and standard deviationCorrect
  3. Cwinsorization at the 5th and 95th percentiles

Explanation

Standardization subtracts the mean and divides by the standard deviation, producing a mean of zero and unit standard deviation. Min-max normalization rescales to a 0-1 range and does not yield those moments. Winsorization limits outliers but does not rescale features.

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