Moutinho / Hutcheson | The SAGE Dictionary of Quantitative Management Research | E-Book | sack.de
E-Book

E-Book, Englisch, 344 Seiten, Format (B × H): 170 mm x 242 mm

Moutinho / Hutcheson The SAGE Dictionary of Quantitative Management Research

E-Book, Englisch, 344 Seiten, Format (B × H): 170 mm x 242 mm

ISBN: 978-1-4462-0960-8
Verlag: SAGE Publications
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)



A must-have reference resource for quantitative management researchers, the Dictionary contains over 100 entries covering the fundamentals of quantitative methodologies; covering both analysis and implementation and examples of use, as well as detailed graphics to aid understanding.
Every entry features:

-An introduction to the topic,

-Key relevant features,

-A worked example,

-A concise summary and a selection of further reading suggestions

-Cross-references to associated concepts within the dictionary
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Weitere Infos & Material


Introduction
A/B Split Testing
Analytic Hierarchy Process
Association and Causation in Quantitative Research
Association Rule Mining
Bass Model
Canonical Correlation
Chaos Theory
Classification and Ranking Belief Simplex
Clustering Algorithms
Cluster Analysis
Coding Conventions for Representing Information
Conceptual Equivalence
Confidence Intervals
Conjoint Analysis
Construct Operationalization Review (CORE)
Correlation Analysis
Correspondence Analysis
Cross-National/Cultural Comparisons
Cross-Sectional Designs
Data Envelopment Analysis in Management
Data Mining
Data Set Structure
Data Transformation
Dempster-Shafer Theory
Designing Experiments
Discriminant Analysis
Dominance Analysis
DS/AHP
Dummy Variable Coding
Event Studies Methodology
Evaluation Research
Experimental Design
Exploratory or Confirmatory Factor Analysis
Factor Analysis
Fuzzy Decision Trees
Fuzzy Sets
Fuzzy Time Series Models
Generalized Linear Mixed Models
Generalized Linear Models
Geodemographics
Geographical Information Systems
Growth Models
Intraclass Correlation Coefficient
Internal and External Validity
Item Response Theory
Item Response Theory for Management
Latent Segments Analysis
Latent Variable Models
Logical Discriminant Models
Logistic Growth Model
Logistic Regression
Logistic Spline Model
Measurement Reliability
Measurement Invariance in Multigroup Research
Measurement Scales
Moderator-Mediator Variable Distinction
Mixture Models
Multi-Attribute Utility/Value Theory
Multidimensional Scaling
Multilevel Models
Multi-Logistic Growth Model
Multinomial Logistic Regression
Multi-State Modelling
Non-Parametric Measures of Association
Optimal Control Models in Management
Ordinary Least-Squares Regression
Panel Design
Paper Versus Electronic Surveys
Parametric Tests
Partial Correlation
Principal Components Analysis
Programme Evaluation
PROMETHEE Method of Ranking Alternatives
Proportional Odds Model
Quantile Estimators
Quantile Estimators - Bootstrap Confidence Intervals
Rasch Model for Measurement
Receiver Operating Characteristic
Response Styles in Cross-National Research
Retail Site Selection
Sampling Equivalence in Cross-National Research
Sample Size for Proportions
Sample Sizes Versus Usable Observations
Self-Organizing Maps
Single-Case Research Designs
Single-Case Single-Baseline Designs
Sngle-Case Multiple-Baseline Designs
Simulation - Discrete Event
Simulation - Methodology
Structural Equation Modelling in Business Management
Structural Equation Modelling in Marketing - Part 1: Introduction and Basic Concepts
Structural Equation Modelling in Marketing - Part 2: Model Calibration
Structural Equation Modelling in Marketing - Part 3: An Example
Study Design
Survey Design
Tabu Search
Testing a Simple Hypothesis
Validity
Variable Precision Rough Sets
Voronoi Diagrams
Web Surveys
Index


Moutinho, Luiz A M
Luiz Moutinhois Foundation Chair of Marketing at the Department of Management, University of Glasgow

Hutcheson, Graeme D
Dr Graeme Hutcheson specialises in the application of statistical models in social science research. He has published widely in management and education, mostly with respect to the use and interpretation of generalized regression models.


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