Linear regression is a data analysis technique for predicting and modelling the relationship between a response dependent quantitative variable and either one independent variable (Simple linear regression) or several explanatory variables (multiple linear regression).
The main assumptions of the model are;
Linearity of two variables.
Normality of residuals.
Constant variability (homoscedasticity)
We are to use data from 619 new born babies.We are interested in predicting their birth weight in terms of gestation period, weight of mother, mother and sex of a baby by fitting a multilple linear regreesion model.