000			02119nam a2200361 4500
001			OTLid0000447
003			MnU
005			20201105133327.0
006			m o d s
008			180907s2017 mnu o 0 0 eng d
040			_aMnU _beng _cMnU
050		4	_aQA1
050		4	_aQA37.3
100	1		_aBlais, Brian _eauthor
245	0	0	_aStatistical Inference For Everyone _cBrian Blais
264		2	_bOpen Textbook Library
264		1	_bBrian Blais
300			_a1 online resource
490	0		_aOpen textbook library.
505	0		_a1 Introduction to Probability -- 2 Applications of Probability -- 3 Random Sequences and Visualization -- 4 Introduction to Model Comparison -- 5 Applications of Model Comparison -- 6 Introduction to Parameter Estimation -- 7 Priors, Likelihoods, and Posteriors -- 8 Common Statistical Significance Tests -- 9 Applications of Parameter Estimation and Inference -- 10 Multi-parameter Models -- 11 Introduction to MCMC -- 12 Concluding Thoughts -- BibliographyAppendix A: Computational AnalysisAppendix B: Notation and StandardsAppendix C: Common Distributions and Their PropertiesAppendix D: Tables
520	0		_aThis is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester of such a course. It is freely available under the Creative Commons License, and includes a software library in Python for making some of the calculations and visualizations easier.
542	1		_fAttribution-ShareAlike
546			_aIn English.
588	0		_aDescription based on online resource
650		0	_aMathematics _vTextbooks
650		0	_aApplied mathematics _vTextbooks
710	2		_aOpen Textbook Library _edistributor
856	4	0	_uhttps://open.umn.edu/opentextbooks/textbooks/447 _zAccess online version
999			_c19830 _d19830