mathematics

Zhiliang Ying

Zhiliang Ying 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 Zhiliang Ying rather than just read about it. In short: Zhiliang Ying (Chinese: 应志良; pinyin: yìng zhìliáng; born April 1960) is a Professor of Statistics in the Department of Statistics, Columbia University. He served as co-chair of the department.

Key takeaways

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

Reference excerpt

Zhiliang Ying (Chinese: 应志良; pinyin: yìng zhìliáng; born April 1960) is a Professor of Statistics in the Department of Statistics, Columbia University. He served as co-chair of the department.

Education and career He received his PhD from Columbia University in 1987, with Tze Leung Lai as his doctoral advisor. He was the Director of the Institute of Statistics at Rutgers University from 1997 to 2001. His wide research interests cover Survival Analysis, Sequential Analysis, Longitudinal Data Analysis, Stochastic Processes, Semiparametric Inference, Biostatistics and Educational Statistics. He is a co-editor of Statistica Sinica and has been Associate Editor of JASA, Statistica Sinica, Annals of Statistics, Biometrics, and Lifetime Data Analysis. Ying has supervised, collaborated with and encouraged many researchers. He has written or co-authored more than 100 research articles in professional journals.

Selected honours and awards Fellow, Institute of Mathematical Statistics (1995 election) Fellow, American Statistical Association (1999 election) The Morningside Gold Medal of Applied Mathematics 2004 The Distinguished Achievement Award 2007, International Chinese Statistical Association

Selected papers Lin, D. Y., Wei, L. J., & Ying, Z. (1993). Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika, 80(3), 557–572. Lin, D. Y., & Ying, Z. (1994). Semiparametric analysis of the additive risk model. Biometrika, 81(1), 61–71. Chang, H. H., & Ying, Z. (1996). A global information approach to computerized adaptive testing. Applied Psychological Measurement, 20(3), 213–229. Jin, Z., Lin, D. Y., Wei, L. J., & Ying, Z. (2003). Rank‐based inference for the accelerated failure time model. Biometrika, 90(2), 341–353. Ying, Z. (1993), A large sample study of rank estimation for censored regression data. The Annals of Statistics, 76–99.

References

Worked examples

Example 1 — a first encounter with Zhiliang Ying

Start with the simplest possible case. Write down what Zhiliang Ying 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 Zhiliang Ying 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 Zhiliang Ying 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 Zhiliang Ying

In research: Zhiliang Ying 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 Zhiliang Ying 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: Zhiliang Ying is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1960 births, 21st-century Chinese science writers, American statisticians, so understanding it makes those chapters shorter.
In everyday life: Look for Zhiliang Ying 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 Zhiliang Ying in 20 minutes

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

Frequently asked questions

What is Zhiliang Ying in simple terms?

Why does Zhiliang Ying 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 Zhiliang Ying?

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 Zhiliang Ying.