000			a
999			_c34915 _d34915
008			251110b xxu||||| |||| 00| 0 eng d
020			_a9781032223827 _c(hbk)
082			_a519.5 _bLAU
100			_aLauritzen, Steffen
245			_aFundamentals of mathematical statistics
260			_bCRC Press, _c2023 _aBoca Raton :
300			_axiii, 244 p. ; _c25 cm. _bill.,
365			_b81.99 _c£ _d117.39
490			_aChapman and Hall/CRC texts in statistical science
504			_aIncludes bibliographical references and index.
520			_aFundamentals of Mathematical Statistics is meant for a standard one-semester advanced undergraduate or graduate-level course in Mathematical Statistics. It covers all the key topics--statistical models, linear normal models, exponential families, estimation, asymptotics of maximum likelihood, significance testing, and models for tables of counts. It assumes a good background in mathematical analysis, linear algebra, and probability but includes an appendix with basic results from these areas. Throughout the text, there are numerous examples and graduated exercises that illustrate the topics covered, rendering the book suitable for teaching or self-study. Features A concise yet rigorous introduction to a one-semester course in Mathematical Statistics Covers all the key topics Assumes a solid background in Mathematics and Probability Numerous examples illustrate the topics Many exercises enhance understanding of the material and enable course use This textbook will be a perfect fit for an advanced course in Mathematical Statistics or Statistical Theory. The concise and lucid approach means it could also serve as a good alternative, or supplement, to existing texts.
650			_aMathematics
650			_aProbability and Statistics
650			_aRegression Analysis
650			_aMathematical statistics
942			_2ddc _cBK