Need for cutting edge statistical modelling for business analytics

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Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/12508

DC Field	Value	Language
dc.contributor.author	Krishna Kumar, Telikicherla
dc.date.accessioned	2020-06-17T14:22:06Z	-
dc.date.available	2020-06-17T14:22:06Z	-
dc.date.issued	2009
dc.identifier.issn	0970-3896
dc.identifier.uri	https://repository.iimb.ac.in/handle/2074/12508	-
dc.description.abstract	Routine statistical modelling seems out of sync with business reality. It does not meet the rigours of efficient modelling in a competitive environment. Cutting-edge data mining methods with new modelling technologies are opening up new opportunities for statisticians in business analytics. The superiority of this new modelling approach over the existing, however, has to be firmly established with a focus on relevance and scientific credibility, which is the aim of this paper.
dc.publisher	Indian Institute of Management Bangalore
dc.subject	Industrial research
dc.subject	Technological innovations
dc.subject	Industrial efficiency
dc.subject	Knowledge management
dc.title	Need for cutting edge statistical modelling for business analytics
dc.type	Journal Article
dc.pages	70-83p.
dc.vol.no	Vol.21	-
dc.issue.no	Iss.1	-
dc.journal.name	IIMB Management Review
Appears in Collections:	2000-2009

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