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R for marketing research and analytics

R for marketing research and analytics (2회 대출)

자료유형
단행본
개인저자
Chapman, Chris. Feit, Elea McDonnell.
서명 / 저자사항
R for marketing research and analytics / Chris Chapman, Elea McDonnell Feit.
발행사항
Cham ;   New York :   Springer,   c2015.  
형태사항
xviii, 454 p. : ill. (some col.) ; 24 cm.
기타형태 저록
Online version:   Chapman, Chris.   R for marketing research and analytics   9783319144368   (211009) 000046035718  
총서사항
Use R!,2197-5736
ISBN
9783319144351 (pbk.) 9783319144368 (ebk.)
요약
"This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications"--Provided by publisher.
일반주기
Online version: Chapman, Chris. R for marketing research and analytics 9783319144368
내용주기
Welcome to R -- The R Language -- Describing Data -- Relationships Between Continuous Variables -- Comparing Groups: Tables and Visualizations -- Comparing Groups: Statistical Tests -- Identifying Drivers of Outcomes: Linear Models -- Reducing Data Complexity -- Additional Linear Modeling Topics -- Confirmatory Factor Analysis and Structural Equation Modeling -- Segmentation: Clustering and Classification -- Association Rules for Market Basket Analysis -- Choice Modeling -- Conclusion -- Appendix: R Versions and Related Software -- Appendix: Scaling up -- Appendix: Packages Used -- Index. .
서지주기
Includes bibliographical references and index.
일반주제명
R (Computer program language). Marketing research --Statistical methods.
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100 1 ▼a Chapman, Chris.
245 1 0 ▼a R for marketing research and analytics / ▼c Chris Chapman, Elea McDonnell Feit.
260 ▼a Cham ; ▼a New York : ▼b Springer, ▼c c2015.
300 ▼a xviii, 454 p. : ▼b ill. (some col.) ; ▼c 24 cm.
490 1 ▼a Use R!, ▼x 2197-5736
504 ▼a Includes bibliographical references and index.
505 0 ▼a Welcome to R -- The R Language -- Describing Data -- Relationships Between Continuous Variables -- Comparing Groups: Tables and Visualizations -- Comparing Groups: Statistical Tests -- Identifying Drivers of Outcomes: Linear Models -- Reducing Data Complexity -- Additional Linear Modeling Topics -- Confirmatory Factor Analysis and Structural Equation Modeling -- Segmentation: Clustering and Classification -- Association Rules for Market Basket Analysis -- Choice Modeling -- Conclusion -- Appendix: R Versions and Related Software -- Appendix: Scaling up -- Appendix: Packages Used -- Index. .
520 ▼a "This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications"--Provided by publisher.
650 0 ▼a R (Computer program language).
650 0 ▼a Marketing research ▼x Statistical methods.
700 1 ▼a Feit, Elea McDonnell.
776 0 8 ▼i Online version: ▼a Chapman, Chris. ▼t R for marketing research and analytics ▼z 9783319144368 ▼w (211009) 000046035718
830 0 ▼a Use R!.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/서고7층/ 청구기호 519.50285 C466r 등록번호 111796045 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

Welcome to R
The R Language
Describing Data
Relationships Between Continuous Variables
Comparing Groups: Tables and Visualizations
Comparing Groups: Statistical Tests
Identifying Drivers of Outcomes: Linear Models
Reducing Data Complexity
Additional Linear Modeling Topics
Confirmatory Factor Analysis and Structural Equation Modeling
Segmentation: Clustering and Classification
Association Rules for Market Basket Analysis
Choice Modeling
Conclusion
Appendix: R Versions and Related Software
Appendix: Scaling up
Appendix: Packages Used
Index.  .

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