This module introduces the foundational concepts of probability, including random events, sample spaces, and probability distributions. It explores how to calculate and interpret probabilities, analyze data using visual tools like bar charts and histograms, and apply conditional probability to real-world scenarios. Learners will develop a strong understanding of probabilistic reasoning and its practical implications.

This module explores the fundamentals of statistical inference through a real-world experiment involving taste testing. Learners will understand how to evaluate evidence, interpret p-values, and make decisions based on probability. It covers key concepts like the null hypothesis, sampling distributions, and significance levels.

This module provides an in-depth look at sampling methods, statistical inference, and how to estimate population parameters using sample data. Learners will explore key concepts such as sampling distributions, standard errors, and hypothesis testing, while gaining the ability to analyze and interpret statistical results in real-world scenarios.

This module delves into the principles of statistical inference and regression analysis, covering key topics such as OLS regression, ANOVA, and the F-distribution. Learners will gain the ability to interpret regression models, understand their statistical foundations, and apply these techniques to real-world data. The module also explores common pitfalls and transformations in regression analysis.

This module examines the limitations of Null Hypothesis Significance Testing (NHST), explores Type I and Type II errors, and introduces the concept of power and inverse probability. It also covers the application of these ideas in interpreting conditional probabilities, particularly in medical testing scenarios. Learners will gain a deeper understanding of statistical reasoning and its real-world implications.

This module explores the principles of sound statistical inference, focusing on the proper interpretation of p-values, the limitations of null hypothesis significance testing, and the role of the American Statistical Association in guiding scientific research. Learners will gain a deeper understanding of how to evaluate and apply statistical methods effectively.