Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

Although [Vitor Fróis] is explaining linear regression because it relates to machine learning, the post and, indeed, the topic have wide applications in many things that we do with electronics ...

Computations that involve matrix algorithms are happening everywhere in the world at every moment in time, whether these be embedded in the training of neural networks in data science, in computer ...

The actual linear regression math is the same whether you want to make a prediction or analyze the strength of a relationship, but it's often useful to make a distinction. In many cases you want to ...

What Are Some Ways Linear Regression Can Be Applied in Business Settings?. During the course of operation, businesses accumulate all kinds of data such as numbers related to sales performance and ...

STAT 3400 - Applied Regression STAT 3400 - Applied Regression Introduces methods, theory, and applications of linear statistical models, covering topics such as estimation, residual diagnostics, ...

Multiple regression and regression diagnostics. Generalised linear models; the exponential family, the linear predictor, link functions, analysis of deviance, parameter estimation, deviance residuals.

The discipline of statistics has deep roots in both mathematics and in substantive scientific fields. Mathematics provides the language in which models and the properties of statistical methods are ...

Linear regression forecasting is a time-series method that uses basic statistics to project future values for a target variable.