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 |