Tools

LEADER 04748cam a2200565 i 4500

001 on1308614139;

003 OCoLC;

005 20250422153007.0;

008 220215s2023 nyua 001 0 eng d;

015 a| GBC2310902| bnb;

016 7 a| 0204952152| Uk;

020 a| 9781265087685q| (paperback);

020 a| 1265087687q| (paperback);

029 0 a| UKMGBb| 020495215;

029 1 a| AU@b| 000072344148;

035 a| (Sirsi) o1308614139;

035 a| (OCoLC)1308614139;

049 a| EREE;

050 4 a| HD30.23b| .J344 2023;

082 04 a| 658.40332| 23;

100 1 a| Jaggia, Sanjiv,d| 1960-e| author.1| https://id.oclc.org/worldcat/entity/E39PCjxmmWcr8PjWvxChvkhGpP1| https://isni.org/isni/0000000038789896=| ^A1478673;

245 10 a| Business analytics :b| communicating with numbers /c| Sanjiv Jaggia (California Polytechnic State University), Alison Kelly (Suffolk University), Kevin Lertwachara (California Polytechnic State University) and Leida Chen (California Polytechnic State University).;

250 a| Second edition.;

250 a| International student edition.;

264 1 a| New York :b| McGraw Hill,c| [2023];

300 a| xxv, 774 pages :b| illustrations (color) ;c| 28 cm.;

336 a| text2| rdacontent;

337 a| unmediated2| rdamedia;

338 a| volume2| rdacarrier;

490 0 a| The McGraw Hill Series in Operations and Decision Sciences;

500 a| Includes index.;

500 a| Previous edition: 2021.;

505 00 g| 1.t| Introduction to Business Analytics --g| 2.t| Data Management and Wrangling --g| 3.t| Summary Measures --g| 4.t| Data Visualization --g| 5.t| Probability and Probability Distributions --g| 6.t| Statistical Inference --g| 7.t| Regression Analysis --g| 8.t| More Topics in Regression Analysis --g| 9.t| Logistic Regression --g| 10.t| Forecasting with Time Series Data --g| 11.t| Introduction to Data Mining --g| 12.t| Supervised Data Mining: k-Nearest Neighbors and Na̐ve Bayes --g| 13.t| Supervised Data Mining: Decision Trees --g| 14.t| Unsupervised Data Mining --g| 15.t| Spreadsheet Modeling --g| 16.t| Risk Analysis and Simulation --g| 17.t| Optimization: Linear Programming --g| 18.t| More Applications in Optimization;

520 a| Business Analytics: Communicating with Numbers was written from the ground up to prepare students to understand, manage, and visualize data, apply the appropriate tools, and communicate findings and their relevance. Unlike other resources that simply repackage statistics and traditional operations research, Jaggia seamlessly threads the topics of data wrangling, descriptive analytics, predictive analytics, and prescriptive analytics into a cohesive whole. Jaggia's 2nd edition was revised based on reviewer feedback to meet the current needs of instructors. This edition has five new chapters and new subsections, like data privacy and data ethics in Chapter 1, and has a stronger focus on Excel and R. A new chapter has been added on spreadsheet modeling and prescriptive analytics is covered across three chapters instead of one for more comprehensive coverage. Holistic analytics processes are emphasized, including dealing with real-life data that is neither "clean" nor "small". For example, a Big Data set of COVID-19 data is presented with a sample of over one million observations that include symptoms, patient demographics, and testing results. Similarly, the importance of storytelling is stressed throughout, to help students develop skills in articulating the business value of analytics by communicating key insights from a nontechnical standpoint. --c| provided by publisher.;

650 0 a| Decision makingx| Statistical methods.=| ^A1032499;

650 0 a| Business planningx| Statistical methods.=| ^A364146;

650 0 a| Industrial managementx| Statistical methods.=| ^A62482;

650 7 a| Decision makingx| Statistical methods.2| fast0| (OCoLC)fst00889068;

650 7 a| Industrial managementx| Statistical methods.2| fast0| (OCoLC)fst00971330;

700 1 a| Lertwachara, Kevin,e| author.1| https://isni.org/isni/0000000496564504=| ^A1478233;

700 1 a| Chen, Leida,e| author.=| ^A1478553;

758 i| has work:a| Business analytics (Text)1| https://id.oclc.org/worldcat/entity/E39PCFXtKTGk9XQFPb46kGBRTd4| https://id.oclc.org/worldcat/ontology/hasWork;

949 a| HD30.23 .J344 2023h| JOYNER48o| jssbi| 30372017667376;

994 a| C0b| ERE;

596 a| 1;

998 a| 6296689;

999 a| HD30.23 .J344 2023w| LCc| 1i| 30372017667376d| 6/25/2026e| 5/20/2026l| JGESm| JOYNERn| 3r| Ys| Yt| JGESBKu| 2/11/2025x| BOOKz| JSTACKSo| .STAFF. jssb;

Business analytics : communicating with numbers / Sanjiv Jaggia (California Polytechnic State University), Alison Kelly (Suffolk University), Kevin Lertwachara (California Polytechnic State University) and Leida Chen (California Polytechnic State University).

Author/creator	Jaggia, Sanjiv, 1960- author.
Other author	Kelly, Alison (Professor of economics), author.
Other author	Lertwachara, Kevin, author.
Other author	Chen, Leida, author.
Format	Book
Edition	Second edition.
Edition	International student edition.
Publication	New York : McGraw Hill, [2023]
Copyright Date	©2023
Description	xxv, 774 pages : illustrations (color) ; 28 cm.
Subjects	Decision making--Statistical methods. Business planning--Statistical methods. Industrial management--Statistical methods.

Series	The McGraw Hill Series in Operations and Decision Sciences
Contents	1. Introduction to Business Analytics -- 2. Data Management and Wrangling -- 3. Summary Measures -- 4. Data Visualization -- 5. Probability and Probability Distributions -- 6. Statistical Inference -- 7. Regression Analysis -- 8. More Topics in Regression Analysis -- 9. Logistic Regression -- 10. Forecasting with Time Series Data -- 11. Introduction to Data Mining -- 12. Supervised Data Mining: k-Nearest Neighbors and Na̐ve Bayes -- 13. Supervised Data Mining: Decision Trees -- 14. Unsupervised Data Mining -- 15. Spreadsheet Modeling -- 16. Risk Analysis and Simulation -- 17. Optimization: Linear Programming -- 18. More Applications in Optimization
Abstract	Business Analytics: Communicating with Numbers was written from the ground up to prepare students to understand, manage, and visualize data, apply the appropriate tools, and communicate findings and their relevance. Unlike other resources that simply repackage statistics and traditional operations research, Jaggia seamlessly threads the topics of data wrangling, descriptive analytics, predictive analytics, and prescriptive analytics into a cohesive whole. Jaggia's 2nd edition was revised based on reviewer feedback to meet the current needs of instructors. This edition has five new chapters and new subsections, like data privacy and data ethics in Chapter 1, and has a stronger focus on Excel and R. A new chapter has been added on spreadsheet modeling and prescriptive analytics is covered across three chapters instead of one for more comprehensive coverage. Holistic analytics processes are emphasized, including dealing with real-life data that is neither "clean" nor "small". For example, a Big Data set of COVID-19 data is presented with a sample of over one million observations that include symptoms, patient demographics, and testing results. Similarly, the importance of storytelling is stressed throughout, to help students develop skills in articulating the business value of analytics by communicating key insights from a nontechnical standpoint. -- provided by publisher.
General note	Includes index.
General note	Previous edition: 2021.
ISBN	9781265087685 (paperback)
ISBN	1265087687 (paperback)

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Business analytics : communicating with numbers / Sanjiv Jaggia (California Polytechnic State University), Alison Kelly (Suffolk University), Kevin Lertwachara (California Polytechnic State University) and Leida Chen (California Polytechnic State University).

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