| Dewey Class |
300.727 |
| Title |
Business Analytics ([EBook] :) : Data Science for Business Problems / / by Walter R. Paczkowski. |
| Author |
Paczkowski, Walter R. |
| Other name(s) |
SpringerLink (Online service) |
| Edition statement |
1st ed. 2021. |
| Publication |
Cham : : Springer International Publishing : : Imprint: Springer, , 2021. |
| Physical Details |
XXXVIII, 387 p. 238 illus., 215 illus. in color. : online resource. |
| ISBN |
9783030870232 |
| Summary Note |
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.: |
| Contents note |
1. Types of Business Problems -- 2. Data for Business Problems -- 3. Beginning Data Handling -- 4. Data Preprocessing -- 5. Data Visualization: The Basics -- 6. OLS Regression Basics -- 7. Time Series Basics -- 8. Statistical Tables -- 9. Advanced Data Handling -- 10. Advanced OLS -- 11. Logistic Regression -- 12. Classification. |
| Mode of acces to digital resource |
Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format. |
| System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users). |
| Internet Site |
https://doi.org/10.1007/978-3-030-87023-2 |
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