Корично изображение Електронна книга

Quantitative models in marketing research /

"Recent advances in data collection and data storage techniques enable marketing researchers to study the characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics and marketing-mix variables." "This book presents t...

Пълно описание

Основен автор: Franses, Philip Hans, 1963-
Други автори: Paap, Richard.
Формат: Електронна книга
Език: English
Публикувано: Cambridge ; New York : Cambridge University Press, 2001.
Предмети:
Marketing research > Mathematical models.
Marketing > Recherche > Mode€les mathematiques.
BUSINESS & ECONOMICS > Marketing > Research.
Marktonderzoek.
Kwantitatieve methoden.
Marketingforschung.
Mathematisches Modell.
Electronic books.
Онлайн достъп: http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=73143
Подобни документи: Print version:: Quantitative models in marketing research.
Съдържание:
  • On marketing research
  • Data
  • Models
  • Features of marketing research data
  • Quantitative models
  • Marketing performance measures
  • A continuous variable
  • A binomial variable
  • An unordered multinomial variable
  • An ordered multinomial variable
  • A limited continuous variable
  • A duration variable
  • A continuous dependent variable
  • The standard Linear Regression model
  • Estimation
  • Estimation by Ordinary Least Squares
  • Estimation by Maximum Likelihood
  • Diagnostics, model selection and forecasting
  • Diagnostics
  • Model selection
  • Forecasting
  • Modeling sales
  • Advanced topics
  • A binomial dependent variable
  • Representation and interpretation
  • Modeling a binomial dependent variable
  • The Logit and Probit models
  • Model interpretation
  • Estimation
  • The Logit model
  • The Probit model
  • Visualizing estimation results
  • Diagnostics, model selection and forecasting
  • Diagnostics
  • Model selection
  • Forecasting
  • Modeling the choice between two brands
  • Advanced topics
  • Modeling unobserved heterogeneity
  • Modeling dynamics
  • Sample selection issues
  • An unordered multinomial dependent variable
  • Representation and interpretation
  • The Multinomial and Conditional Logit models
  • The Multinomial Probit model
  • The Nested Logit model
  • Estimation
  • The Multinomial and Conditional Logit models
  • The Multinomial Probit model
  • The Nested Logit model
  • Diagnostics, model selection and forecasting
  • Diagnostics
  • Model selection
  • Forecasting.

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