LEADER 04337nam  22006735  450 
001 9910986128303321
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010   $a9783031780707$b(electronic bk.)
010   $z9783031780691
024 7 $a10.1007/978-3-031-78070-7
035   $a(MiAaPQ)EBC31946255
035   $a(Au-PeEL)EBL31946255
035   $a(CKB)37783626900041
035   $a(OCoLC)1504743238
035   $a(DE-He213)978-3-031-78070-7
035   $a(EXLCZ)9937783626900041
100   $a20250305d2025      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aApplied Statistics and Multivariate Data Analysis for Business and Economics $eA Modern Approach Using R, SPSS, Stata, and Excel /$fby Thomas Cleff
205   $a2nd ed. 2025.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025.
215   $a1 online resource (538 pages)
225 1 $aSpringer Texts in Business and Economics,$x2192-4341
311 08$aPrint version: Cleff, Thomas Applied Statistics and Multivariate Data Analysis for Business and Economics Cham : Springer,c2025 9783031780691 
327   $aChapter 1. Statistics and Empirical Research -- Chapter 2. From Disarray to Dataset -- Chapter 3. Univariate Data Analysis -- Chapter 4. Bivariate Association -- Chapter 5. Classical Measurement Theory -- Chapter 6. Calculating Probability -- Chapter 7. Random Variables and Probability Distributions -- Chapter 8. Parameter Estimation -- Chapter 9. Hypothesis Testing -- Chapter 10. Regression Analysis -- Chapter 11. Logistic Regression -- Chapter 12. Time Series and Indices -- Chapter 13. Cluster Analysis -- Chapter 14. Factor Analysis.
330   $aThis comprehensive textbook equips students of economics and business, as well as industry professionals, with essential principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Through real-world business examples, it illustrates the practical use of univariate, bivariate, and multivariate statistical methods. The content spans a broad range of topics, from data collection and scaling to the presentation and fundamental univariate analysis of quantitative data, while also demonstrating advanced analytical techniques for exploring multivariate relationships. The book systematically covers all topics typically included in university-level courses on statistics and advanced applied data analysis. Beyond theoretical discussion, it offers hands-on guidance for using statistical software tools such as Excel, SPSS, Stata, and R. In this completely revised and updated second edition, new sections on logistic regression are included, along with enhanced examples and solutions using R for all covered statistical methods. This edition provides a robust resource for mastering applied statistics in both academic and professional settings.
410  0$aSpringer Texts in Business and Economics,$x2192-4341
606   $aEconometrics
606   $aQuantitative research
606   $aStatistics
606   $aSocial sciences$xStatistical methods
606   $aMathematical statistics$xData processing
606   $aEconometrics
606   $aData Analysis and Big Data
606   $aStatistics in Business, Management, Economics, Finance, Insurance
606   $aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
606   $aStatistics and Computing
615  0$aEconometrics.
615  0$aQuantitative research.
615  0$aStatistics.
615  0$aSocial sciences$xStatistical methods.
615  0$aMathematical statistics$xData processing.
615 14$aEconometrics.
615 24$aData Analysis and Big Data.
615 24$aStatistics in Business, Management, Economics, Finance, Insurance.
615 24$aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
615 24$aStatistics and Computing.
676   $a330.015195
700   $aCleff$b Thomas$0721665
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
912   $a9910986128303321
996   $aApplied Statistics and Multivariate Data Analysis for Business and Economics$92100377
997   $aUNINA