mathematics

Xinping Cui

Xinping Cui 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 Xinping Cui rather than just read about it. In short: Xinping Cui is a biostatistician focusing on metagenomics and associated problems in high-dimensional inference and data analysis including the multiple comparisons problem. Originally from China, she works in the US as a professor of statistics at the University of California, Riverside.

Key takeaways

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

Reference excerpt

Xinping Cui is a biostatistician focusing on metagenomics and associated problems in high-dimensional inference and data analysis including the multiple comparisons problem. Originally from China, she works in the US as a professor of statistics at the University of California, Riverside. She is a former chair of the university's Department of Statistics, and the director of the Riverside Statistical Consulting Collaboratory.

Education and career Cui graduated from Nankai University in 1994, with a bachelor's degree in mathematics. She earned a master's degree in mathematics from Nankai University in 1997, and a second master's degree in applied statistics from Bowling Green State University in 1998. She went to the University of California, Los Angeles for doctoral study in biostatistics, completing her Ph.D. in 2002. Her dissertation, Quantitative trait linkage analysis of Saccharomyces cerevisiae gene expression data, was supervised by David Elashoff. While at UCLA, she also worked as a statistical analyst in the UCLA Reed Neurological Research Center. After completing her doctorate, she became an assistant professor at the University of California, Riverside, where she was tenured in 2008. She was chair of the university's Department of Statistics from 2015 to 2021.

Recognition Cui is an Elected Member of the International Statistical Institute. She was named as a Fellow of the American Statistical Association in 2023.

References

External links Cui Lab

Worked examples

Example 1 — a first encounter with Xinping Cui

Start with the simplest possible case. Write down what Xinping Cui 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 Xinping Cui 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 Xinping Cui 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 Xinping Cui

In research: Xinping Cui 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 Xinping Cui 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: Xinping Cui is common in secondary-school and first-year university syllabi. It links to neighbouring topics American biostatisticians, American women statisticians, Biostatisticians, so understanding it makes those chapters shorter.
In everyday life: Look for Xinping Cui 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.

Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Xinping Cui” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Xinping Cui in 20 minutes

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

Frequently asked questions

What is Xinping Cui in simple terms?

Why does Xinping Cui 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 Xinping Cui?

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 Xinping Cui.