000			01464nam a2200229Ia 4500
003			OSt
005			20220228160210.0
008			220128s9999 xx 000 0 und d
020			_a9781849969529
040			_cCUS
082			_a519.2 _bDEK/M
100			_aDekking, F.M. _94204
245		0	_a A Modern Introduction to Probability and Statistics: Understanding why and How
260			_aLondon: _c2005 _bSpringer,
300			_axv, 487p.
505			_aWhy probability and statistics?.- Outcomes, events, and probability.- Conditional probability and independence.- Discrete random variables.- Continuous random variables.- Simulation.- Expectation and variance.- Computations with random variables.- Joint distributions and independence.- Covariance and correlation.- More computations with more random variables.- The Poisson process.- The law of large numbers.- The central limit theorem.- Exploratory data analysis: graphical summaries.- Exploratory data analysis: numerical summaries.- Basic statistical models.- The bootstrap.- Unbiased estimators.- Efficiency and mean squared error.- Maximum likelihood.- The method of least squares.- Confidence intervals for the mean.- More on confidence intervals.- Testing hypotheses: essentials.- Testing hypotheses: elaboration.- The t-test.- Comparing two samples.
700			_94121 _aKraaikamp, C.
700			_94122 _aLopuhaa, H.P.
700			_aMeester, L.E. _94123
942			_2ddc _cWB16
947			_a5399
999			_c211220 _d211220