000 02971nam a2200445Ia 4500
001 2696
008 230305s2015 xx 000 0 und d
020 _a9783319144351
043 _aen_UK
041 _aeng
245 0 _aR for marketing research and analytics
260 _a
_bSpringer,
_c2015
300 _aXVIII, 454 p.; 23 cm
505 _aWelcome to R
_rThe R Language--
_rDescribing Data--
_rRelationships Between Continuous Variables--
_rComparing Groups: Tables and Visualizations--
_rComparing Groups: Statistical Tests--
_rIdentifying Drivers of Outcomes: Linear Models--
_rReducing Data Complexity--
_rAdditional Linear Modeling Topics--
_rConfirmatory Factor Analysis and Structural Equation Modeling--
_rSegmentation: Clustering and Classification--
_rAssociation Rules for Market Basket Analysis--
_rChoice Modeling--
_rConclusion--
_rAppendix: R Versions and Related Software--
_rAppendix: Scaling up--
_rAppendix: Packages Used--
_rIndex.--
_r--
520 _aThis 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.
630 _aHF COMMERCE
_914
650 0 _aStatistics
_92152
650 _aMathematical statistics
_92592
650 0 _aStatistics
_xEconomic aspects
_92591
650 _a
_9794
650 0 _aManagement
_9319
650 _a
_9794
650 0 _aEconomics
_92587
650 _a
_9794
650 0 _aFinance
_93911
650 _a
_9794
650 _aInsurance
_911877
650 0 _aStatistics
_xComputer programs
_911878
650 _aStatistics Programs
_911879
650 _a
_912
650 0 _aMarketing
_91020
700 _aMcDonnell Feit, Elea
_eAuthor
_911880
700 _aChapman, Chris
_eAuthor
_911881
902 _a352
905 _am
912 _a2015-01-01
942 _a1
953 _d2019-10-23 18:20:17
999 _c2598
_d2598