000 02670cam a2200373Ia 4500
001 u13525
003 SA-PMU
005 20210418125032.0
008 161213s2016 flua 001 0 eng d
040 _aSINAP
_beng
_cSINAP
_dOCLCO
_dIBK
_dOCLCQ
_dFIE
_dRIU
020 _a9781466591653
020 _a146659165X
035 _a(OCoLC)965870076
050 4 _aHD38.7
_bB37 2016
082 1 4 _a658.472
100 1 _aBasu, Ayanendranath.
245 1 2 _aA user's guide to business analytics /
_cAyanendranath Basu, Srabashi Basu.
260 _aBoca Raton, FL :
_bCRC Press,
_c©2016.
300 _axvi, 384 pages :
_billustrations ;
_c25 cm
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
520 _aA User's Guide to Business Analytics provides a comprehensive discussion of statistical methods useful to the business analyst. Methods are developed from a fairly basic level to accommodate readers who have limited training in the theory of statistics. A substantial number of case studies and numerical illustrations using the R-software package are provided for the benefit of motivated beginners who want to get a head start in analytics as well as for experts on the job who will benefit by using this text as a reference book. The book is comprised of 12 chapters. The first chapter focuses on business analytics, along with its emergence and application, and sets up a context for the whole book. The next three chapters introduce R and provide a comprehensive discussion on descriptive analytics, including numerical data summarization and visual analytics. Chapters five through seven discuss set theory, definitions and counting rules, probability, random variables, and probability distributions, with a number of business scenario examples. These chapters lay down the foundation for predictive analytics and model building. --
_cProvided by publisher.
505 0 _aWhat is analytics? -- Intorducing R -- An analytics software -- Reporting data -- Statistical graphics and visual analytics -- Probability -- Random variables and probability distributions -- Continuous random variables -- Statistical inference -- Regression for predictive model building -- Decision trees -- Data mining and multivariate methods -- Modeling time series data for forecasting.
650 0 _aDecision making
_xStatistical methods.
650 0 _aBusiness planning
_xStatistical methods.
650 0 _aR (Computer program language)
650 0 _aData mining.
700 1 _aBasu, Srabashi.
942 _cBOOK
994 _aZ0
_bSUPMU
948 _hNO HOLDINGS IN SUPMU - 9 OTHER HOLDINGS
596 _a1 2
999 _c11017
_d11017