Nolan graduated from Vassar College in 1977;[2] she gained her first experience in statistics in a summer job at Vassar, doing statistical analyses for author Caroline Bird. After graduating, she began working as an applications programmer for IBM. Needing to learn more statistics for her work, she studied at Columbia University for a year, and then entered full-time graduate study in statistics at Yale University.[3] At Yale, the applied side of her research included work confirming the logarithmic spiral shape of snail shells.[3] Her dissertation, supervised by David Pollard,[4] concerned central limit theorems,[3] and was titled U-Processes.[4] She completed her Ph.D. in 1986, and became a faculty member at Berkeley in the same year,[2] the first new female regular-rank faculty member in the department since Elizabeth Scott in 1951.[3]
Books
Nolan is the author of several statistics books:
Stat Labs: Mathematical Statistics Through Applications (with Terry Speed, Springer, 2000)[5]
Teaching Statistics: A Bag of Tricks (with Andrew Gelman, Oxford University Press, 2002)[6]
XML and Web Technologies for Data Sciences with R (with Duncan Temple Lang, Springer, 2014)[7]
Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (with Duncan Temple Lang, CRC Press, 2015)
↑Reviews of Stat Labs: Mathematical Statistics Through Applications: Subhabrata Chakraborti (2001), Technometrics 43 (3): 378–379, doi:10.1198/tech.2001.s635; Jay Devore (2001), The American Statistician 55 (3): 257–258, doi:10.1198/tas.2001.s122; Somesh Das Gupta (February 2002), Sankhyā: The Indian Journal of Statistics, Series A 64 (1): 175–177, JSTOR25051381.
↑Review of Teaching Statistics: A Bag of Tricks: Richard J. Cleary (2005), The American Statistician 59 (3): 275, doi:10.1198/tas.2005.s245.
↑Review of XML and Web Technologies for Data Sciences with R: Simon Munzert (2014), Journal of Statistical Software 61, doi:10.18637/jss.v061.b01.
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