mathematics

Statistical epidemiology

Statistical epidemiology is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Statistical epidemiology rather than just read about it. In short: Statistical epidemiology is an emerging branch of the disciplines of epidemiology and biostatistics that aims to: Bring more statistical rigour to bear in the field of epidemiology Recognise the importance of applied statistics, especially with respect to the context in which statistical methods are appropriate and inappropriate Aid and improve our interpretation of observations Introduction The science of epidemiol…

Key takeaways

Statistical epidemiology belongs to mathematics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Statistical epidemiology to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Statistical epidemiology from memory before moving on to harder problems.

Reference excerpt

Statistical epidemiology is an emerging branch of the disciplines of epidemiology and biostatistics that aims to:

Bring more statistical rigour to bear in the field of epidemiology Recognise the importance of applied statistics, especially with respect to the context in which statistical methods are appropriate and inappropriate Aid and improve our interpretation of observations

Introduction The science of epidemiology has had enormous growth, particularly with charity and government funding. Many researchers have been trained to conduct studies, requiring multiple skills ranging from liaising with clinical staff to the statistical analysis of complex data, such as using Bayesian methods. The role of a Statistical Epidemiologist is to bring the most appropriate methods available to bear on observational study from medical research, requiring a broad appreciation of the underpinning methods and their context of applicability and interpretation. The earliest mention of this phrase was in an article by EB Wilson, taking a critical look at the way in which statistical methods were developing and being applied in the science of epidemiology.

Academic recognition There are two Professors of Statistical Epidemiology in the United Kingdom (University of Leeds and Imperial College, London) and a Statistical Epidemiology group (Oxford University).

Related fields Statistical epidemiology draws upon quantitative methods from fields such as: statistics, operations research, computer science, economics, biology, and mathematics.

Worked examples

Example 1 — a first encounter with Statistical epidemiology

Start with the simplest possible case. Write down what Statistical epidemiology claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Statistical epidemiology before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Statistical epidemiology ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Statistical epidemiology

In research: Statistical epidemiology appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Statistical epidemiology in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Statistical epidemiology is common in secondary-school and first-year university syllabi. It links to neighbouring topics Biostatistics, Demography, Epidemiology, so understanding it makes those chapters shorter.
In everyday life: Look for Statistical epidemiology outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Statistical epidemiology in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Statistical epidemiology means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Statistical epidemiology out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Statistical epidemiology in simple terms?

Statistical epidemiology is an emerging branch of the disciplines of epidemiology and biostatistics that aims to: Bring more statistical rigour to bear in the field of epidemiology Recognise the importance of applied statistics, especially with respect to the context in which statistical methods ar…

Why does Statistical epidemiology matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Statistical epidemiology?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Statistical epidemiology.