Buch, Englisch, 487 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 762 g
Reihe: Use R!
Buch, Englisch, 487 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 762 g
Reihe: Use R!
ISBN: 978-3-030-14315-2
Verlag: Springer International Publishing
Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis.
With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.
The 2nd edition increases the book’s utility for students and instructors with the inclusion of exercises and classroom slides. At the same time, it retains all of the features that make it a vital resource for practitioners: non-mathematical exposition, examples modeled on real world marketing problems, intuitive guidance on research methods, and immediately applicable code.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen
- Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
- Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Marketing
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
Weitere Infos & Material
Chapter 1: Welcom to R.- Chapter 2: An Overview of the R Language.- Chapter 3: Describing Data.- Chapter 4: Relationships Between Continuous Variables.- Chapter 5: Comparing Groups: Tables and Visualizations.- Chapter 6: Comparing Groups: Statistical Tests.- Chapter 7: Identifying Drivers of Outcomes: Linear Models.- Chapter 8: Reducing Data Complexity.- Chapter 9: Assorted Linear Modeling Topics.- Chapter 10: Confirmatory Factor Analysis and Structural Equation Modeling.- Chapter 11: Segmentation: Clustering and Classification.- Chapter 12: Association Rules for Market Basket Analysis.- Chapter 13: Choice Modeling.- Chapter 14: Marketing Mix Models.- Appendix A: R Versions and Related Software.- Appendix B: Scaling Up.- Appendix C: Packages Used.- Appendix D: Online Materials and Data Files.