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-making. In both traditional ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Mitchell Grant is a self-taught investor with over 5 years of experience as a financial trader. He is a financial content strategist and creative content editor. Timothy Li is a consultant, accountant ...

SERC copy Purchased with Adopt-a-Book funds. "Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the ...

What are the different types of predictive modeling? Your email has been sent Predictive modeling is a type of data mining that is used in a variety of situations and industries. This process involves ...

Interview with Dr. Caroline Buckee on the uses — and limitations — of epidemiologic modeling to predict the spread of Covid-19. 10m 49s Download Amid enormous uncertainty about the future of the Covid ...