Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

In epidemiological studies using linear regression, it is often necessary for reasons of economy or unavailability of data to use as the independent variable not the variable ideally demanded by the ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

Vol. 18, Analytic and Geometric Stochastics: Papers in Honour of G. E. H. Reuter (Dec., 1986), pp. 73-85 (13 pages) A construction due to Asmussen and Jacobsen is generalised so as to produce ...

At times it is desirable to have independent variables in the model that are qualitative rather than quantitative. This is easily handled in a regression framework. Regression uses qualitative ...

To predict a continuous target variable (like crop yield, house price, etc.) using multiple independent features (e.g., temperature, humidity, rainfall). This is an extension of simple linear ...

Overview This project builds a Linear Regression model to predict Canada's per capita income for the year 2020 using historical data. The dataset is sourced from canada_per_capita_income.csv. Dataset ...