Linear regression is a statistical method used to understand the relationship between an outcome variable and one or more explanatory variables. It works by fitting a regression line through the ...

Multiple Linear Regression In linear regression, when there's just a single independent variable, the analysis is sometimes called simple linear regression to distinguish the analysis from situations ...

I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

The most basic regression relationship is a simple linear regression. In this case, E (Y | X) = μ (X) = β0 + β1X, a line with intercept β0 and slope β1.

In a simple regression with one independent variable, that coefficient is the slope of the line of best fit. In this example or any regression with two independent variables, the slope is a mix of ...

Nonlinear regression is a form of regression analysis in which data is fit to a model and then expressed as a mathematical function. Simple linear regression relates two variables (X and Y) with a ...

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...