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

Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels.

Linear algebra is essential for understanding core data science concepts like machine learning, neural networks, and data ...

Any home gardener knows they have to tailor their watering regime for different plants. Forgetting to water their flowerbed ...

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 ...

Generalized Linear Models (GLMs) and Categorical Data Analysis (CDA) Course Topics Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and ...

Regression is a method to estimate parameters in mathematical models of biological systems from experimental data. To ensure the validity of a model for a given data set, pre-regression and post ...

One useful tool to help us make sense of these kinds of problems is regression. Regression is a statistical method that allows us to look at the relationship between two variables, while holding other ...

Topics include: general theory of regression and generalised linear models, linear regression, logistic regression for binary data, models for ordered and unordered (nominal) responses, log-linear ...