What is re-expressing data?

What is re-expressing data?

What is meant by re-expressing data? Re-expressing data means making the data more suitable for analysis by our methods.

What is the purpose of re-expressing or transforming data?

Straight to the Point Often re-expression (transformation) can save the day, straightening bent relationships so that we can fit and use a simple linear model. Two simple ways to re-express data are with logarithms and reciprocals.

What type of data often benefits from re-expression by taking the logarithm of values?

What type of data often benefits from re-expression by taking the logarithm of values? Data that can not be negative. Usually values that grow by percentage rates. When re-expressing, start with logs and then look at the residual plot to see which direction to go in.

What does a random residual plot mean?

A residual plot is a graph that shows the residuals on the vertical axis and the independent variable on the horizontal axis. If the points in a residual plot are randomly dispersed around the horizontal axis, a linear regression model is appropriate for the data; otherwise, a nonlinear model is more appropriate.

What is the ladder of powers?

The Tukey ladder of powers (sometimes called the Bulging Rule) is a way to change the shape of a skewed distribution so that it becomes normal or nearly-normal. It can also help to reduce error variability (heteroscedasticity). Tukey (1977) created a table of powers (numbers to which data can be raised).

What is a power model?

Power model: a function with equation of the form y = axn or a/xn. Direct variation power model: a function with equation y = axn (n > 0), for example, the relationship between volume of a cube and edge length is modeled by a direct variation function.

Why do we use residuals?

Residuals are important when determining the quality of a model. You can examine residuals in terms of their magnitude and/or whether they form a pattern. Where the residuals are all 0, the model predicts perfectly. The further residuals are from 0, the less accurate the model.