Which Transformation?

Explore and select appropriate data transformations based on different analytical objectives and data characteristics.

Language

Transform Data

How to Start

Step 1

Select the characteristics of your study and/or dataset using the checkboxes.

Step 2

The tool will automatically filter and suggest suitable transformations.

Step 3

Click on a suggested transformation to view detailed information and its mathematical formula.

Step 4

Use this information to decide which transformation best fits your data and analysis goals.

Suggested Transformations

32

Box-Cox Yeo-Johnson Tukey's Ladders Power Guerrero-Johnson Inverse/Reciprocal Square Root Cubic Root Logarithmic Log-Sinh Log-Log Log-Log Complementar Logarithmic Return Kinetic Negative Logarithmic Normal Scores Exponential By Positions Z-Score Normalization Decimal Scale Robust Scale Absolute Maximum Scale Min-Max Normalization Unit Length Scale Probability Integral Whitening Arc Sine Square Root Sine Arc Folded Exponential Probit Logit chiPower Isometric Logratio

Characteristics

Selected Filters:

Analysis Distributions Objectives Data Type Value Range Data Format

Linear Regression t-test ANOVA Generalised linear model Survival Analysis Logistic Regression Quantile Regression Neural Network Support Vector Machine Principal component analysis Discriminant Analysis k-nearest neighbours k-means independent component analysis

Formula

About

This work was developed as a result of the dissertation 'Comprehensive Analysis of Data Transformation Methods', from the Master's Degree in Biostatistics and Biometrics at Universidade Aberta Of Portugal (Distance Learning University).