3 D Statistical Learning

Making Statistical Concepts Accessible – Edition 13: Logistic Regression in R, Interpreting the Output

When conducting analysis with a binary outcome, it is essential to align the interpretation of the results with the goal of the analysis, whether it’s inference or prediction. Unlike linear regression, the output of logistic…

Making Statistical Concepts Accessible – Edition 14: Cloglog and Probit as Alternatives to Logit Link Function

Introduction In social sciences, health sciences, and fields like banking and insurance, logistic regression remains a popular method for prediction and inference, especially when the outcome variable is binary. Logistic regression, a specific case of…

Making Statistical Concepts Accessible – Edition 15: Modeling Count Data with the Poisson Distribution

In public health data analysis, disease counts, proportions, and rates are often used as outcome variables. These discrete outcomes differ from the continuous variables typically associated with linear regression. When analyzing count data, especially when…