What is the product moment correlation coefficient?
- The product moment correlation coefficient (PMCC) is a way of giving a numerical value to linear correlation of bivariate data
At AS Level you learned how to use linear regression models to describe a relationship between two variables. However, it is possible for two variables to have a relationship that does not fit a linear model, but still shows a pattern based on exponential growth or decay. A linear regression model is only appropriate if the PMCC is close to 1 or -1.
What forms can non – linear regression models take?
- If a bivariate data set appears to have a non – linear relationship it could fit an exponential model
How can non – linear regression models be used?
- Non – linear regression models can be used in much the same way as linear regression models
- By coding the original data using logarithms (changing the variables) a regression line of Y on X can be found
- This can be used to make predictions for data values that are within the range of the given data (interpolation)
- Making a prediction outside of the range of the given data is called extrapolation and should not be done