LEADER 02222nam 2200481 450 001 9910830979903321 005 20231110232352.0 010 $a1-119-71496-6 010 $a1-119-71494-X 010 $a1-119-71492-3 035 $a(CKB)4100000011920393 035 $a(MiAaPQ)EBC6579278 035 $a(Au-PeEL)EBL6579278 035 $a(OCoLC)1250077209 035 $a(EXLCZ)994100000011920393 100 $a20211213d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModern industrial statistics $ewith applications in R, MINITAB and JMP /$fRon. S Kenett and Shelemyahu Zacks 205 $a3rd ed. 210 1$aHoboken, New Jersey :$cWiley,$d[2021] 210 4$dİ2021 215 $a1 online resource (883 pages) 225 1 $aStatistics in Practice 311 $a1-119-71490-7 320 $aIncludes bibliographical references and index. 330 $a"Industrial Statistics is concerned with maintaining and improving the quality of goods and services. It involves a broad range of statistical tools but maintaining and improving quality is its main concern. Variability is inherent in all processes, whether they be manufacturing processes or service processes. This variability must be controlled to create high quality goods and services and must be reduced to improve quality. Industrial Statistics focuses on the use of statistical thinking, i.e., the appreciation of the inherent variability of all processes in order that all possible outcomes can be assessed. It also focuses on developing skills for modeling data and designing experiments that can lead to improvements in performance and reductions in variablity"--$cProvided by publisher. 410 0$aStatistics in Practice 606 $aQuality control$xStatistical methods 615 0$aQuality control$xStatistical methods. 676 $a658.562 700 $aKenett$b Ron$0874200 702 $aZacks$b Shelemyahu$f1932- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830979903321 996 $aModern industrial statistics$94054698 997 $aUNINA