LEADER 03952nam 22007575 450 001 9910647396003321 005 20250610124005.0 010 $a3-031-11833-2 024 7 $a10.1007/978-3-031-11833-3 035 $a(MiAaPQ)EBC7188465 035 $a(Au-PeEL)EBL7188465 035 $a(CKB)26076434900041 035 $a(DE-He213)978-3-031-11833-3 035 $a(PPN)267811020 035 $a(EXLCZ)9926076434900041 100 $a20230130d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntroduction to Statistics and Data Analysis $eWith Exercises, Solutions and Applications in R /$fby Christian Heumann, Michael Schomaker, Shalabh 205 $a2nd ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (584 pages) 311 08$aPrint version: Heumann, Christian Introduction to Statistics and Data Analysis Cham : Springer International Publishing AG,c2023 9783031118326 320 $aIncludes bibliographical references and index. 327 $aPart I Descriptive Statistics: Introduction and Framework -- Frequency Measures and Graphical Representation of Data -- Measures of Central Tendency and Dispersion -- Association of Two Variables -- Part I Probability Calculus: Combinatorics -- Elements of Probability Theory -- Random Variables -- Probability Distributions -- Part III Inductive Statistics: Inference -- Hypothesis Testing -- Linear Regression -- Logistic Regression -- Part IV Additional Topics Simple Random Sampling and Bootstrapping -- Causality -- Part V Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries. 330 $aNow in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications. 606 $aStatistics 606 $aQuantitative research 606 $aStatistics 606 $aStatistics$xComputer programs 606 $aStatistical Theory and Methods 606 $aData Analysis and Big Data 606 $aApplied Statistics 606 $aStatistical Software 606 $aEstadística$2thub 606 $aEconometria$2thub 606 $aMacroeconomia$2thub 606 $aR (Llenguatge de programació)$2thub 608 $aLlibres electrònics$2thub 615 0$aStatistics. 615 0$aQuantitative research. 615 0$aStatistics. 615 0$aStatistics$xComputer programs. 615 14$aStatistical Theory and Methods. 615 24$aData Analysis and Big Data. 615 24$aApplied Statistics. 615 24$aStatistical Software. 615 7$aEstadística 615 7$aEconometria 615 7$aMacroeconomia 615 7$aR (Llenguatge de programació) 676 $a330.015195 676 $a519.5 700 $aHeumann$b Christian$f1962-$01351244 702 $aSchomaker$b Michael 702 $aShalabh 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910647396003321 996 $aIntroduction to Statistics and Data Analysis$93091262 997 $aUNINA