LEADER 03373nam 2200505 450 001 9910830160203321 005 20200601171148.0 010 $a1-119-55154-4 010 $a1-119-55158-7 010 $a1-119-55155-2 035 $a(CKB)4100000008869881 035 $a(MiAaPQ)EBC5844284 035 $a(PPN)254673171 035 $a(OCoLC)1117710100 035 $a(CaSebORM)9781119551522 035 $a(EXLCZ)994100000008869881 100 $a20190911d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied statistics $etheory and problem solutions with R /$fDieter Rasch, Rob Verdooren, Ju?rgen Pilz 205 $a1st edition 210 1$aHoboken, New Jersey ;$aChichester, West Sussex, England :$cWiley,$d[2020] 210 4$dİ2020 215 $a1 online resource (512 pages) 311 $a1-119-55152-8 320 $aIncludes bibliographical references and index. 330 $aInstructs readers on how to use methods of statistics and experimental design with R software Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong theoretical background, but it is practically oriented to develop one's ability to tackle new and non-standard problems confidently. Taking a practical approach to applied statistics, this user-friendly guide teaches readers how to use methods of statistics and experimental design without going deep into the theory. Applied Statistics: Theory and Problem Solutions with R includes chapters that cover R package sampling procedures, analysis of variance, point estimation, and more. It follows on the heels of Rasch and Schott's Mathematical Statistics via that book's theoretical background?taking the lessons learned from there to another level with this book?s addition of instructions on how to employ the methods using R. But there are two important chapters not mentioned in the theoretical back ground as Generalised Linear Models and Spatial Statistics. Offers a practical over theoretical approach to the subject of applied statistics Provides a pre-experimental as well as post-experimental approach to applied statistics Features classroom tested material Applicable to a wide range of people working in experimental design and all empirical sciences Includes 300 different procedures with R and examples with R-programs for the analysis and for determining minimal experimental sizes Applied Statistics: Theory and Problem Solutions with R will appeal to experimenters, statisticians, mathematicians, and all scientists using statistical procedures in the natural sciences, medicine, and psychology amongst others. 606 $aMathematical statistics$vProblems, exercises, etc 606 $aR (Computer program language) 615 0$aMathematical statistics 615 0$aR (Computer program language) 676 $a519.5 700 $aRasch$b Dieter$0102778 702 $aVerdooren$b L. R. 702 $aPilz$b Ju?rgen$f1951- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830160203321 996 $aApplied statistics$93939419 997 $aUNINA