Introduces methods, theory and applications of statistical models, from linear models (simple and multiple linear regression), to hierarchical linear models. Topics such as estimation, residual ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision ...

Drug development enterprise is struggling because of prohibitively high costs and slow progress. There is urgent need for adoption of novel adaptive designs to improve the efficiency and success of ...

As we enter a world of machine learning and data science, are there any gotchas or negatives? It sounds as if it is all sunshine and rainbows, but, as the title to this post alludes, I believe there ...

In predictive modeling, future events are predicted based on statistical analysis. Read this guide to understand how predictive modeling works and how it can benefit your business. Image: ...