Social forskning og statistik
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Python for Marketing Research and Analytics
Udgivet af Springer Nature Switzerland AG
ISBN
9783030497224
Om denne bog
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, …
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Bogdetaljer
Forfatter
Chris Chapman, Jason S. Schwarz, Elea McDonnell Feit
Forlag
Springer Nature Switzerland AG
Kategori
Social forskning og statistik
ISBN-13
9783030497224
EAN
9783030497224
Format
Hæftet
Sprog
Engelsk
sider
272
Produktbeskrivelse
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.
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