Linear regression is one of the most widely used basic statistical methods. With its help, we can study relationship between causes and an effect that is measurable on a quantitative scale within analyzed dependence. This is a help when making purely practical decisions about technical details of the relationship under study and it can be used for forecasting.
Join our webinar and find out:
❖ how to build a linear regression model step by step,
❖ how to avoid pitfalls,
❖ how to understand details of a model obtained.
We will present examples in the Statistica program.
