國立虎尾科技大學 |

Quantitative models in marketing research /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Quantitative models in marketing research // Philip Hans Franses and Richard Paap.
作者:	Franses, Philip Hans,
其他作者:	Paap, Richard,
面頁冊數:	1 online resource (xiii, 206 pages) :digital, PDF file(s). :
附註:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
標題:	Marketing research - Mathematical models. -
電子資源:	https://doi.org/10.1017/CBO9780511753794
ISBN:	9780511753794 (ebook)

Quantitative models in marketing research /
Franses, Philip Hans,1963-

Quantitative models in marketing research /Philip Hans Franses and Richard Paap. - 1 online resource (xiii, 206 pages) :digital, PDF file(s).

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

On marketing research --

Advances in data collection and data storage techniques have enabled marketing researchers to study the individual characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics. This 2001 book presents important and practically relevant quantitative models for marketing research. Each model is presented in detail with a self-contained discussion, which includes: a demonstration of the mechanics of the model, empirical analysis, real world examples, and interpretation of results and findings. The reader of the book will learn how to apply the techniques, as well as understand the methodological developments in the academic literature. Pathways are offered in the book for students and practitioners with differing numerical skill levels; a basic knowledge of elementary numerical techniques is assumed.

ISBN: 9780511753794 (ebook)Subjects--Topical Terms:

1446730
Marketing research
--Mathematical models.

LC Class. No.: HF5415.2 / .F714 2001

Dewey Class. No.: 658.8/3/015118

Quantitative models in marketing research /
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500 $a Title from publisher's bibliographic system (viewed on 05 Oct 2015).
505 0 0 $t On marketing research -- $t Data -- $t Models -- $t Features of marketing research data -- $t Quantitative models -- $t Marketing performance measures -- $t A continuous variable -- $t A binomial variable -- $t An unordered multinomial variable -- $t An ordered multinomial variable -- $t A limited continuous variable -- $t A duration variable -- $t A continuous dependent variable -- $t The standard Linear Regression model -- $t Estimation -- $t Estimation by Ordinary Least Squares -- $t Estimation by Maximum Likelihood -- $t Diagnostics, model selection and forecasting -- $t Diagnostics -- $t Model selection -- $t Forecasting -- $t Modeling sales -- $t Advanced topics -- $t A binomial dependent variable -- $t Representation and interpretation -- $t Modeling a binomial dependent variable -- $t The Logit and Probit models -- $t Model interpretation -- $t Estimation -- $t The Logit model -- $t The Probit model -- $t Visualizing estimation results -- $t Diagnostics, model selection and forecasting -- $t Diagnostics -- $t Model selection -- $t Forecasting -- $t Modeling the choice between two brands -- $t Advanced topics -- $t Modeling unobserved heterogeneity -- $t Modeling dynamics -- $t Sample selection issues -- $t An unordered multinomial dependent variable -- $t Representation and interpretation -- $t The Multinomial and Conditional Logit models -- $t The Multinomial Probit model -- $t The Nested Logit model -- $t Estimation -- $t The Multinomial and Conditional Logit models -- $t The Multinomial Probit model -- $t The Nested Logit model -- $t Diagnostics, model selection and forecasting -- $t Diagnostics -- $t Model selection -- $t Forecasting.
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