A Little Bit of Everything in Biostatistics for Health Science Students

A Little Bit of Everything in Biostatistics for Health Science Students#

By Payton Yau, Suhirthakumar Puvanendran, and Jarunee Nualyong | Version 1.0#

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An Applied Open-Source Textbook for Health Science Undergraduates, Epidemiology Students, and Self-Directed Learners in Public Health

About This Book#

Most biostatistics textbooks are written for mathematics students. This book is written for people who want to understand disease — and prevent it.

To give you a complete picture of public health research, this book is built around two historically influential datasets representing the two halves of epidemiology:

  1. Observational Epidemiology: A teaching subset of the Framingham Heart Study, the longest-running cardiovascular epidemiology study in history. Since 1948, researchers in Framingham, Massachusetts have followed thousands of participants to identify the risk factors for heart disease — high blood pressure, high cholesterol, smoking, diabetes, obesity — concepts so fundamental to modern medicine that we have forgotten they had to be discovered.

  2. Experimental Epidemiology: The Anorexia Clinical Trial dataset. This tracks patients undergoing psychological therapies, allowing us to test interventions and prove whether a treatment actually changes a physiological outcome (body weight).

This book uses that dataset to teach statistics the way it should be taught: through real variables with real clinical meanings, where a regression slope tells you something about survival, and a Chi-Square result tells you something about who is most at risk.

What You Will Learn#

By the end of this book you will be able to:

  • Classify any health variable at the correct level of measurement

  • Calculate and interpret descriptive statistics and confidence intervals

  • Select and run the correct statistical test for any research scenario

  • Interpret p-values, effect sizes, and confidence intervals correctly

  • Produce and read Kaplan-Meier survival curves and log-rank tests

  • Use PSPP and R to analyse real epidemiological data

The Dataset#

  1. The Framingham Heart Study Teaching Subset — 500 participants, 22 variables, baseline examination.

Data derived from the Framingham Heart Study teaching dataset, provided by the National Heart, Lung, and Blood Institute (NHLBI/NIH) for educational purposes. Original study: Framingham Heart Study (N01-HC-25195). This teaching subset is for educational use only and is not appropriate for research publication.

# Load the dataset in R
fram_data <- read.csv("data/framingham_teaching.csv")

  1. The Clinical Trial Dataset (Anorexia) — 72 participants, 3 variables, before-and-after treatment.

This dataset tracks weight changes in young female patients undergoing treatments for anorexia nervosa. It is built directly into R’s MASS package, requiring no external downloads.

# Load the built-in dataset in R (MASS is pre-installed)
library(MASS)
data(anorexia)

How This Book Is Organised#

The book is divided into four parts across nine chapters:

Part I — Describing the World in Numbers (Chapters 1–3): What kind of data do we have? How do we summarise it? How confident can we be in our estimates?

Part II — Testing What We Think We Know (Chapters 4–6): What are the laws of chance? How do we test a hypothesis? How do we compare two groups?

Part III — Comparing More Than Two Groups (Chapters 7–8): How do we compare three or more groups? How do we measure and model relationships?

Part IV — Putting It All Together (Chapter 9): How do we select the right test? How do we read and report survival data? What have we learned?

How to Use This Book#

Each chapter follows the same structure: a plain-English introduction, worked examples using the Framingham data, a lab manual in both PSPP and R, a Test Your Knowledge exercise with a dropdown solution, key terms, review questions, and a summary.

You do not need a mathematics background. You need curiosity about disease and the patience to work through examples.

A Little Bit of Everything in Biostatistics for Health Science Students is an open-source textbook. It is free to read, use, and adapt under its open licence. Source files are available at the GitHub repository linked above.

Contents