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Business analytics = data science fo...

Paczkowski, Walter R.

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Business analytics = data science for business problems /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Business analytics/ by Walter R. Paczkowski.
Reminder of title:	data science for business problems /
Author:	Paczkowski, Walter R.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xxxviii, 387 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Decision making - Mathematical models. -
Online resource:	https://doi.org/10.1007/978-3-030-87023-2
ISBN:	9783030870232

Business analytics = data science for business problems /
Paczkowski, Walter R.

Business analyticsdata science for business problems /[electronic resource] :by Walter R. Paczkowski. - Cham :Springer International Publishing :2021. - xxxviii, 387 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783030870232

Standard No.: 10.1007/978-3-030-87023-2doiSubjects--Topical Terms:

565918
Decision making
--Mathematical models.

LC Class. No.: HD30.23 / .P33 2021

Dewey Class. No.: 658.4033

Business analytics = data science for business problems /
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245 1 0 $a Business analytics $h [electronic resource] : $b data science for business problems / $c by Walter R. Paczkowski.
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300 $a xxxviii, 387 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Decision making $x Mathematical models. $3 565918
650 1 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 3382132
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650 2 4 $a Probability and Statistics in Computer Science. $3 891072
650 2 4 $a Online Marketing/Social Media. $3 2181685
650 2 4 $a Consumer Behavior. $3 3220217
650 2 4 $a Market Research/Competitive Intelligence. $3 2162287
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