LEADER 03783nam 22006615 450 001 9910254083103321 005 20250410110450.0 010 $a3-319-46162-1 024 7 $a10.1007/978-3-319-46162-5 035 $a(CKB)3710000001041182 035 $a(DE-He213)978-3-319-46162-5 035 $a(MiAaPQ)EBC6312567 035 $a(MiAaPQ)EBC5577863 035 $a(Au-PeEL)EBL5577863 035 $a(OCoLC)1066180234 035 $a(PPN)198342063 035 $a(EXLCZ)993710000001041182 100 $a20170127d2016 u| 0 101 0 $aeng 135 $aurnn|008mamaa 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 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (XIII, 456 p. 89 illus.) 311 08$a3-319-46160-5 320 $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 -- Part IV Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries. 330 $aThis 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. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. 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 all methodsto their own applications. 606 $aStatistics 606 $aStatistics 606 $aEconometrics 606 $aMacroeconomics 606 $aStatistical Theory and Methods 606 $aStatistics in Business, Management, Economics, Finance, Insurance 606 $aEconometrics 606 $aMacroeconomics and Monetary Economics 615 0$aStatistics. 615 0$aStatistics. 615 0$aEconometrics. 615 0$aMacroeconomics. 615 14$aStatistical Theory and Methods. 615 24$aStatistics in Business, Management, Economics, Finance, Insurance. 615 24$aEconometrics. 615 24$aMacroeconomics and Monetary Economics. 676 $a519.5 700 $aHeumann$b Christian$4aut$4http://id.loc.gov/vocabulary/relators/aut$0755947 702 $aSchomaker$b Michael$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aShalabh$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254083103321 996 $aIntroduction to Statistics and Data Analysis$92182318 997 $aUNINA