LEADER 01456nas 22004093a 450 001 996335982403316 005 20240413025210.0 035 $a(CKB)991042723590002 035 $a(CONSER)---00212757- 035 $a(EXLCZ)99991042723590002 100 $a20000912b2000200u --- a 101 0 $aeng 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aHealth information compliance insider 210 $aNew York, NY $cBrownstone Publishers, Inc.$dc2000- 215 $a1 online resource 300 $aTitle from caption. 311 08$aPrint version: Health information compliance insider. 1531-6009 (DLC) 00212757 (OCoLC)44997263 531 0 $aHealth inf. compliance insid. 606 $aMedical informatics$zUnited States$vPeriodicals 606 $aMedical records$xManagement$vPeriodicals 606 $aMedical informatics$2fast$3(OCoLC)fst01014175 606 $aMedical records$xManagement$2fast$3(OCoLC)fst01014564 607 $aUnited States$2fast$1https://id.oclc.org/worldcat/entity/E39PBJtxgQXMWqmjMjjwXRHgrq 608 $aPeriodicals.$2fast 615 0$aMedical informatics 615 0$aMedical records$xManagement 615 7$aMedical informatics. 615 7$aMedical records$xManagement. 676 $a346 906 $aJOURNAL 912 $a996335982403316 920 $aexl_impl conversion 996 $aHealth information compliance insider$92299200 997 $aUNISA LEADER 04201nam 22005655 450 001 9910484208903321 005 20200703030339.0 010 $a3-030-39278-3 024 7 $a10.1007/978-3-030-39278-9 035 $a(CKB)4920000000496075 035 $a(DE-He213)978-3-030-39278-9 035 $a(MiAaPQ)EBC6168052 035 $a(PPN)243762526 035 $a(EXLCZ)994920000000496075 100 $a20200409d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExcel 2019 for Engineering Statistics $eA Guide to Solving Practical Problems /$fby Thomas J. Quirk 205 $a2nd ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XVII, 250 p. 166 illus., 161 illus. in color.) 225 1 $aExcel for Statistics,$x2570-4605 311 $a3-030-39277-5 327 $aPreface -- Acknowledgements -- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 2 Random Number Generator -- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- 4 One-Group t-Test for the Mean -- 5 Two-Group t-Test of the Difference of the Means for Independent Groups -- 6 Correlation and Simple Linear Regression -- 7 Multiple Correlation and Multiple Regression -- 8 One-Way Analysis of Variance (ANOVA) -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-table -- Index. 330 $aNewly revised to specifically address Microsoft Excel 2019, this book shows the capabilities of Excel in teaching engineering statistics effectively. Similar to the previously published Excel 2016 for Engineering Statistics, this volume is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical engineering problems. Excel, a widely available computer program for students and professionals, is also an effective teaching and learning tool for quantitative analyses in engineering courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Engineering Statistics capitalizes on these improvements by teaching readers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand engineering problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full practice test (with answers in an appendix) that allows readers to test what they have learned. This new edition features a wealth of new sample problems and solutions, as well as updated chapter content throughout. 410 0$aExcel for Statistics,$x2570-4605 606 $aStatistics 606 $aApplied mathematics 606 $aEngineering mathematics 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 606 $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008 606 $aMathematical and Computational Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11006 615 0$aStatistics. 615 0$aApplied mathematics. 615 0$aEngineering mathematics. 615 14$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aStatistics and Computing/Statistics Programs. 615 24$aMathematical and Computational Engineering. 676 $a519.5 700 $aQuirk$b Thomas J$4aut$4http://id.loc.gov/vocabulary/relators/aut$0721655 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484208903321 996 $aExcel 2019 for Engineering Statistics$92347960 997 $aUNINA