The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

We review recent results for high-dimensional sparse linear regression in the practical case of unknown variance. Different sparsity settings are covered, including coordinate-sparsity, group-sparsity ...

General results are obtained for an approximation to the variance of a weighted regression estimator in which the weights are sample estimators of unknown unpatterned variances. Independent normally ...

Linear regression remains a cornerstone of statistical analysis, offering a framework for modelling relationships between a dependent variable and one or more independent predictors. Over the past ...

Description: Use of existing computer programs and subroutines to solve statistical problems. Areas of application include analysis of variance, linear and nonlinear regression analysis, nonparametric ...

Description: This course will explore fundamental concepts of statistical methods and their application in biological research. The following topics will be included: experimental and sampling designs ...