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Bhavesh Badani

Bhavesh Badani

03-May-2024

Mathematical Approach:

  • We start with our original data, denoted as (x).
  • The Box-Cox transformation raises this data to a power (an exponent), denoted as (\lambda): [ f(x) = {x^lambda - 1}{lambda} {(for positive data)}  and for negative data
  • we use a modified formula:

f(x)=((x+c)^−1)​/λ

where c is a constant added to make the data positive.

where c is a constant added to make the data positive.

  • (c) is a constant added to make the data positive (for negative data).
  • We choose (lambda) to optimize normality (make the data look more like a bell curve).

Simplified Explanation:

  • Imagine you have data that doesn’t quite follow a normal distribution.
  • The Box-Cox transformation helps you find the right power (lambda) to apply to your data so that it becomes more “normal.”
  • It’s like adjusting the knobs on a radio until you get the clearest signal !
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