03437oam 2200517 450 991048332640332120220630164749.03-030-49720-810.1007/978-3-030-49720-0(CKB)4100000011558765(DE-He213)978-3-030-49720-0(MiAaPQ)EBC6383549(PPN)252509544(EXLCZ)99410000001155876520210416d2020 uy 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierPython for marketing research and analytics /Jason S. Schwarz, Chris Chapman and Elea McDonnell Feit1st ed. 2020.Cham, Switzerland :Springer,[2020]©20201 online resource (XI, 272 p. 90 illus., 79 illus. in color.)3-030-49719-4 Includes bibliographical references and index.Part I: Basics of Python -- Chapter 1: Welcome to Python -- Chapter 2: The Python Language -- Part II Fundamentals of Data Analysis -- 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: Additional Linear Modeling Topics -- Part III Advanced data analysis -- Chapter 9: Reducing Data Complexity -- Chapter 10: Segmentation: Unsupervised Clustering Methods for Exploring Subpopulations -- Chapter 11: Classification: Assigning observations to known categories -- Chapter 12: Conclusion -- Index.This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab notebooks, which integrate code, figures, tables, and annotation in a single file. The code notebooks for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research. This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics. .Python (Computer program language)Marketing researchComputer programsR (Computer program language)Python (Computer program language)Marketing researchR (Computer program language).519.5Schwarz Jason S.1065735Feit Elea McDonnellChapman ChrisMiAaPQMiAaPQUtOrBLWBOOK9910483326403321Python for marketing research and analytics2547738UNINA