000			02131nam a2200349 4500
001			OTLid0000287
003			MnU
005			20201105133313.0
006			m o d s
008			180907s2014 mnu o 0 0 eng d
020			_a9781491907337
040			_aMnU _beng _cMnU
050		4	_aQA76
100	1		_aDowney, Allen B. _eauthor
245	0	0	_aThink Stats _bProbability and Statistics for Programmers _cAllen Downey
264		2	_bOpen Textbook Library
264		1	_bGreen Tea Press
300			_a1 online resource
490	0		_aOpen textbook library.
505	0		_aPreface -- 1 Exploratory data analysis -- 2 Distributions -- 3 Probability mass functions -- 4 Cumulative distribution functions -- 5 Modeling distributions -- 6 Probability density functions -- 7 Relationships between variables -- 8 Estimation -- 9 Hypothesis testing -- 10 Linear least squares -- 11 Regression -- 12 Time series analysis -- 13 Survival analysis -- 14 Analytic methods
520	0		_aThink Stats is an introduction to Probability and Statistics for Python programmers. Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets. If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.
542	1		_fAttribution-NonCommercial
546			_aIn English.
588	0		_aDescription based on online resource
650		0	_aComputer Science _vTextbooks
710	2		_aOpen Textbook Library _edistributor
856	4	0	_uhttps://open.umn.edu/opentextbooks/textbooks/287 _zAccess online version
999			_c19687 _d19687