A+ » VCE » Further Maths U3 & 4 Master Notes » A1 Data Analysis » 3.6 Introduction to Data Transformations

# 3.6 Introduction to Data Transformations

Contents

### Linearization

• So far we have only looked at methods of analysing linear associations and not non-linear associations. Luckily, linearization provides a convenient way of transforming non-linear associations into linear ones so that they can be analysed using the same methods.
• Linearization works by applying a transformation of some form to either the explanatory and/or response variables datasets. In Further Maths, you will only deal with situations requiring one of the datasets to be transformed at a time.
• Keep in mind that the formula for the linearised model must include the transformation (e.g. the formula for a model which has undergone a square transformation to the explanatory variable will be of the form y=a+bx^2).

### Square Transformation

This content is for Master Notes FM members only. Unlock the content by signing up for a membership level - quick and easy!