| 000 | 08013nam a22007211i 4500 | ||
|---|---|---|---|
| 001 | 8355743 | ||
| 003 | IEEE | ||
| 005 | 20200413152930.0 | ||
| 006 | m eo d | ||
| 007 | cr cn |||m|||a | ||
| 008 | 180502s2018 caua foab 000 0 eng d | ||
| 020 |
_a9781681733210 _qebook |
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| 020 |
_z9781681733203 _qpaperback |
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| 020 |
_z9781681733227 _qhardcover |
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| 024 | 7 |
_a10.2200/S00838ED1V01Y201803ENG030 _2doi |
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| 035 | _a(CaBNVSL)swl00408285 | ||
| 035 | _a(OCoLC)1033620112 | ||
| 040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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| 050 | 4 |
_aHF5415.2 _b.A333 2018 |
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| 082 | 0 | 4 |
_a658.83 _223 |
| 100 | 1 |
_aAkinkunmi, Mustapha, _eauthor. |
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| 245 | 1 | 0 |
_aData mining and market intelligence : _bimplications for decision making / _cMustapha Akinkunmi. |
| 264 | 1 |
_a[San Rafael, California] : _bMorgan & Claypool, _c2018. |
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| 300 |
_a1 PDF (xxii, 159 pages) : _billustrations. |
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| 336 |
_atext _2rdacontent |
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| 337 |
_aelectronic _2isbdmedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 490 | 1 |
_aSynthesis lectures on engineering, _x1939-523X ; _v# 30 |
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| 538 | _aMode of access: World Wide Web. | ||
| 500 | _aPart of: Synthesis digital library of engineering and computer science. | ||
| 504 | _aIncludes bibliographical references (pages 157-158). | ||
| 505 | 0 | _a1. Introduction to market intelligence -- 1.1 Understanding the link between marketing insights and decision making -- 1.2 Transform data into insights for decisions: segmentation, positioning, product development, etc. -- 1.3 Market intelligence tools -- 1.4 Scientific method and technology of marketing research -- 1.5 Innovative solutions to real-life issues -- 1.6 Designing the research methodology, questionnaire, sampling plan, and data analysis -- 1.7 Turning data into strategic insights -- 1.8 Exercises -- | |
| 505 | 8 | _a2. The market research process -- 2.1 The marketing research framework and process -- 2.2 Research problems and correct design techniques -- 2.3 Data collection methods -- 2.4 Generating marketing insights -- 2.5 Exercises -- | |
| 505 | 8 | _a3. Qualitative techniques -- 3.1 Self-administered method -- 3.2 Personal interview or face-to-face method -- 3.3 Exercises -- | |
| 505 | 8 | _a4. Quantitative techniques -- 4.1 Data preparation and descriptive statistics -- 4.2 Fundamentals of quantitative methods and their applications -- 4.3 Concept of distribution pattern, central tendency, and dispersion -- 4.3.1 Distribution pattern -- 4.3.2 Measure of central tendency -- 4.3.3 Measure of dispersion -- 4.4 Construction of confidence intervals -- 4.4.1 Application of confidence intervals -- 4.5 Other descriptive statistics -- 4.5.1 Skewness -- 4.5.2 Kurtosis -- 4.6 Exercises -- | |
| 505 | 8 | _a5. Hypothesis testing and regression analysis -- 5.1 Data preparation and evaluation for quantitative analysis -- 5.2 Constructing and testing data hypotheses -- 5.3 Regression analysis: concept and applications (interpret data relationships and forecasting) -- 5.3.1 Assumptions of linear regression -- 5.3.2 Simple linear regression -- 5.3.3 Multiple regression -- 5.3.4 Assumptions of multiple regression -- 5.4 Exercises -- | |
| 505 | 8 | _a6. Analyzing survey data -- 6.1 Quantitative technique of collecting survey data: consumer expenditure survey -- 6.2 Types of measurement scales and their applications -- 6.3 Survey research rigor -- 6.4 Testing data quality: survey error detection procedures -- 6.5 Exercises -- | |
| 505 | 8 | _a7. Index methodology -- 7.1 Bra expectation index: principles, techniques, and applications -- 7.1.1 Objectives of bra expectation index -- 7.1.2 Methodology -- 7.1.3 Calculation of bra expectation index -- 7.2 Bra consumer confidence index: principles, techniques, and applications -- 7.2.1 Components of braCCI -- 7.2.2 Methodology -- 7.2.3 Illustrative example -- 7.2.4 Index maintenance -- 7.3 BraIndex: principles, techniques, and applications -- 7.3.1 Basic criteria for selection of constituent stocks -- 7.3.2 Technical criteria -- 7.3.3 Fundamental selection criteria -- 7.3.4 Corporate event -- 7.3.5 Stock splits adjustment barometer -- 7.3.6 Free-float -- 7.3.7 Calculation of braIndex -- 7.3.8 Illustrative example -- 7.3.9 Measure of braIndex volatility -- 7.3.10 Index maintenance -- 7.4 Bra producer price index: principles, techniques, and applications -- 7.4.1 Uses of braPPI -- 7.4.2 Components of braPPI -- 7.4.3 Scope and coverage -- 7.4.4 Collection of data -- 7.4.5 Index calculation -- 7.4.6 Illustrative example -- 7.5 Bra bond index: principles, techniques, and applications -- 7.5.1 Definition of terms -- 7.5.2 Basic criteria for constituent bonds -- 7.5.3 Index calculation -- 7.5.4 Sub-indices -- 7.5.5 Illustrative example -- 7.6 BraInflation index: principles, techniques, and applications -- 7.6.1 Uses of bra inflation index -- 7.6.2 Classification of braII items -- 7.6.3 Period of the survey -- 7.6.4 Data collection, collation, and processing -- 7.6.5 Quality adjustment -- 7.6.6 Index calculation -- 7.6.7 Bra inflation indices publication -- 7.6.8 Expenditure category weight -- 7.6.9 Illustrative example -- 7.7 Exercises -- | |
| 505 | 8 | _a8. Digital media monitoring, measurement, and modeling -- 8.1 Understandings of social media monitoring, measurement, and modeling -- 8.2 Strategic insight of social media monitoring -- 8.3 Social media measurement -- 8.4 Social media modeling -- 8.5 Exercises -- | |
| 505 | 8 | _a9. Causal methods -- 9.1 Marketing mix modeling: concept, principles, methods, and applications -- 9.2 Effective communication of research, intelligence, and analytic insights -- 9.3 Exercises -- | |
| 505 | 8 | _a10. Mobile data mining -- 10.1 Concept of mobile data mining -- 10.2 Activities of mobile data mining -- 10.3 Architecture of mobile data mining -- 10.4 Algorithms of mobile data mining -- 10.5 Application of mobile data mining -- 10.6 Exercises -- | |
| 505 | 8 | _aA. Questionnaires, items survey, and weights of elementary items -- Sample of business expectation survey questionnaire -- List of items survey monthly -- Weights of some items -- Bibliography -- Author's biography. | |
| 506 | _aAbstract freely available; full-text restricted to subscribers or individual document purchasers. | ||
| 510 | 0 | _aCompendex | |
| 510 | 0 | _aINSPEC | |
| 510 | 0 | _aGoogle scholar | |
| 510 | 0 | _aGoogle book search | |
| 520 | 3 | _aThis book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of market intelligence, this book is designed to inspire and inform readers on how to conduct market intelligence by leveraging data and technology, supporting smart decision making.The book explains some suitable methodologies for data analysis that are based on robust statistical methods. For illustrative purposes, the author uses real-life data for all the examples in this book. In addition, the book discusses the concepts, techniques, and applications of digital media and mobile data mining. Hence, this book is a guide tool for policy makers, academics, and practitioners whose areas of interest are statistical inference, applied statistics, applied mathematics, business mathematics, quantitative techniques, and economic and social statistics. | |
| 530 | _aAlso available in print. | ||
| 588 | _aTitle from PDF title page (viewed on May 2, 2018). | ||
| 650 | 0 |
_aMarketing research _xData processing. |
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| 650 | 0 | _aData mining. | |
| 653 | _adata mining | ||
| 653 | _adecision making | ||
| 653 | _amarket intelligence | ||
| 653 | _amarket pooling | ||
| 653 | _asurvey | ||
| 655 | 0 | _aElectronic books. | |
| 776 | 0 | 8 |
_iPrint version: _z9781681733227 _z9781681733203 |
| 830 | 0 | _aSynthesis digital library of engineering and computer science. | |
| 830 | 0 |
_aSynthesis lectures on engineering ; _v# 30. _x1939-523X |
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| 856 | 4 | 2 |
_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/servlet/opac?bknumber=8355743 |
| 999 |
_c562373 _d562373 |
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