mathematics

John Chambers (statistician)

John Chambers (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 John Chambers (statistician) rather than just read about it. In short: John McKinley Chambers (born April 28, 1941) is the creator of the S programming language, and core member of the R programming language project. He was awarded the 1998 ACM Software System Award for developing S.

Key takeaways

John Chambers (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 John Chambers (statistician) to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of John Chambers (statistician) from memory before moving on to harder problems.

Reference excerpt

John McKinley Chambers (born April 28, 1941) is the creator of the S programming language, and core member of the R programming language project. He was awarded the 1998 ACM Software System Award for developing S.

Early life John McKinley Chambers was born on April 28, 1941, in Toronto, Ontario. He received a Bachelor of Science from the University of Toronto in 1963. He received a Master of Arts in 1965 and a PhD degree in 1966, both in statistics, from Harvard University.

Career Chambers started at Bell Laboratories in 1966 as a member of its technical staff. From 1981 to 1983, he was the head of its Advanced Software Department and from 1983 to 1989 he was the head of its Statistics and Data Analysis Research Department. In 1989, he moved back to full-time research and in 1995, he became a distinguished member of the technical staff. In 1997, he was made the first Fellow of Bell Labs and was cited for "pioneering contributions to the field of statistical computing". He remained a distinguished member of the technical staff and a Fellow until his retirement from Bell Labs in 2005. After retiring from Bell Labs, Chambers became a visiting professor at the University of Auckland, University of California, Los Angeles and Stanford University. Since 2008, he has been active at Stanford, currently serving as Senior Advisor of its data science program and an adjunct professor in Stanford's Department of Statistics. Chambers is a Fellow of the American Statistical Association, the American Association for the Advancement of Science and the Institute of Mathematical Statistics.

Awards and accomplishments Chambers has received the following awards:

1998, awarded the ACM Software System Award for developing the S programming language. The award was presented on May 15, 1999. 2004, awarded an honorary Doctor of Mathematics degree from the University of Waterloo

John M. Chambers Statistical Software Award Following his 1998 ACM Software System Award, Chambers donated his prize money (US$10,000) to the American Statistical Association to endow an award for novel statistical software, the John M. Chambers Statistical Software Award.

Bibliography Chambers, John M. (1977). Computational methods for data analysis. New York: Wiley. ISBN 0-471-02772-3. Chambers, John M. (1983). Graphical methods for data analysis. Belmont, Calif: Wadsworth International Group. ISBN 0-534-98052-X. Chambers, John M. (1984). Compstat lectures: lectures in computational statistics. Heidelberg: Physica. ISBN 3-7051-0006-8. Becker, R.A.; Chambers, J.M. (1984). S: An Interactive Environment for Data Analysis and Graphics. Pacific Grove, CA, USA: Wadsworth & Brooks/Cole. ISBN 0-534-03313-X. Becker, R.A.; Chambers, J.M. (1985). Extending the S System. Pacific Grove, CA, USA: Wadsworth & Brooks/Cole. ISBN 0-534-05016-6. Becker, R.A.; Chambers, J.M.; Wilks, A.R. (1988). The New S Language: A Programming Environment for Data Analysis and Graphics. Pacific Grove, CA, USA: Wadsworth & Brooks/Cole. ISBN 0-534-09192-X. Chambers, J.M.; Hastie, T.J. (1991). Statistical Models in S. Pacific Grove, CA, USA: Wadsworth & Brooks/Cole. p. 624. ISBN 0-412-05291-1. Chambers, John M. (1998). Programming with data: a guide to the S language. Berlin: Springer. ISBN 0-387-98503-4. Chambers, John M. (2008). Software for data analysis programming with R. Berlin: Springer. ISBN 978-0-387-75935-7. Chambers, John M. (2016). Extending R. Florida: Chapman and Hall/CRC. p. 382. ISBN 978-1498775717.

References

Worked examples

Example 1 — a first encounter with John Chambers (statistician)

Start with the simplest possible case. Write down what John Chambers (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 John Chambers (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 John Chambers (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 John Chambers (statistician)

In research: John Chambers (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 John Chambers (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: John Chambers (statistician) is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1941 births, Computational statisticians, Fellows of the American Association for the Advancement of Science, so understanding it makes those chapters shorter.
In everyday life: Look for John Chambers (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 John Chambers (statistician) in 20 minutes

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

Frequently asked questions

What is John Chambers (statistician) in simple terms?

Why does John Chambers (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 John Chambers (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 John Chambers (statistician).