mathematics

Xihong Lin

Xihong Lin 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 Xihong Lin rather than just read about it. In short: Xihong Lin (Chinese: 林希虹) is a Chinese–American statistician known for her contributions to mixed models, nonparametric and semiparametric regression, and statistical genetics and genomics. As of 2015, she is the Henry Pickering Walcott Professor and Chair of the Department of Biostatistics at Harvard T.H.

Key takeaways

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

Reference excerpt

Xihong Lin (Chinese: 林希虹) is a Chinese–American statistician known for her contributions to mixed models, nonparametric and semiparametric regression, and statistical genetics and genomics. As of 2015, she is the Henry Pickering Walcott Professor and Chair of the Department of Biostatistics at Harvard T.H. Chan School of Public Health and Coordinating Director of the Program in Quantitative Genomics. Lin received the COPSS Presidents' Award in 2006, the Spiegelman award of the outstanding health statistician from the American Public Health Association in 2002, and the MERIT Award from the National Cancer Institute (2007-2016). Lin was elected a fellow of the American Statistical Association in 2000 and of the Institute of Mathematical Statistics in 2007, and an elected member of the International Statistical Institute in 2006. She won the Florence Nightingale David Award of the Committee of Presidents of Statistical Societies in 2017 "for leadership and collaborative research in statistical genetics and bioinformatics; and for passion and dedication in mentoring students and young statisticians". Lin was elected to the National Academy of Medicine in 2018 and National Academy of Sciences in 2023. Lin received her BSc from Tsinghua University in 1989 and her PhD in biostatistics from the University of Washington in 1994, where her supervisor was Norman Breslow. Her dissertation was Bias Correction in Generalized Linear Mixed Models.

References

External links Xihong Lin's home page

Illustrations

Worked examples

Example 1 — a first encounter with Xihong Lin

Start with the simplest possible case. Write down what Xihong Lin 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 Xihong Lin 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 Xihong Lin 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 Xihong Lin

In research: Xihong Lin 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 Xihong Lin 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: Xihong Lin is common in secondary-school and first-year university syllabi. It links to neighbouring topics 20th-century births, 21st-century American women, American statisticians, so understanding it makes those chapters shorter.
In everyday life: Look for Xihong Lin 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 Xihong Lin in 20 minutes

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

Frequently asked questions

What is Xihong Lin in simple terms?

Why does Xihong Lin 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 Xihong Lin?

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 Xihong Lin.