mathematics

Ruth King (statistician)

Ruth King (statistician) 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 Ruth King (statistician) rather than just read about it. In short: Ruth King (née Langham) FRSE FLSW is the current Thomas Bayes' Chair of Statistics in the School of Mathematics at the University of Edinburgh, having held the position since 2015. Prior to this she held positions at the University of Cambridge and the University of St Andrews.

Key takeaways

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

Reference excerpt

Ruth King (née Langham) FRSE FLSW is the current Thomas Bayes' Chair of Statistics in the School of Mathematics at the University of Edinburgh, having held the position since 2015. Prior to this she held positions at the University of Cambridge and the University of St Andrews.

Her main research interests are "Capture-recapture; Bayesian inference; hidden (semi-)Markov models; state-space models; missing data; applications in ecology and epidemiology".Her research focuses on the development of novel statistical techniques applied to a range of different application areas, particularly within ecology, epidemiology or medicine. This research is often interdisciplinary in nature, relying on strong collaborative links with other researchers.She was recognised by the Royal Society of Edinburgh as one of Scotland's leading female scientists in their exhibition and elected as a Fellow in 2018. She was also elected a fellow of the Learned Society of Wales in 2017, and a Fellow of the Institute of Mathematical Statistics in 2022.

Career and research She graduated with a BSc in Mathematics with Statistics in 1998, and completed a PhD in 2001, both from the University of Bristol. In her final year of undergraduate she was awarded the 'Henry Ronald Hasse Prize'. Her PhD was supervised by Steve Brooks. Following her PhD she worked as a research associate at the University of Cambridge, from 2001 to 2003. From 2003 to 2005, she was an EPSRC post-doctoral fellow. From 2003 to 2010, she was a lecturer in Statistics at the University of St Andrews, then a reader in Statistics from 2010 to 2015. Currently, she is the Thomas Bayes' Chair of Statistics at the University of Edinburgh, a post she has held since 2015. She has spoken at numerous Conferences, in a number of countries, throughout her career. In 2019, she co-organised the ICMS workshop on "Addressing Statistical Challenges of Modern Technological Advances" as well as the "Global Expert Working Group on Multiple Systems Estimation of Modern Slavery" in Edinburgh. She has 69 publications on "Google Scholar" since 2001, with a total of 1370 citations since 2014 (as of June 2019), and 2213 citations overall. Since 2017 she has been part of the team delivering the University of Edinburgh's 'Unlocking the World of Data' course on edX

References

Worked examples

Example 1 — a first encounter with Ruth King (statistician)

Start with the simplest possible case. Write down what Ruth King (statistician) 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 Ruth King (statistician) 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 Ruth King (statistician) 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 Ruth King (statistician)

In research: Ruth King (statistician) 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 Ruth King (statistician) 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: Ruth King (statistician) is common in secondary-school and first-year university syllabi. It links to neighbouring topics 21st-century British statisticians, Alumni of the University of Bristol, Biostatisticians, so understanding it makes those chapters shorter.
In everyday life: Look for Ruth King (statistician) 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 Ruth King (statistician) in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Ruth King (statistician) 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 Ruth King (statistician) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Ruth King (statistician) in simple terms?

Why does Ruth King (statistician) 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 Ruth King (statistician)?

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 Ruth King (statistician).