LEADER 02807nam 2200649 a 450 001 9910974448603321 005 20240516121117.0 010 $a9786613293497 010 $a9781283293495 010 $a1283293498 010 $a9781907830617 010 $a1907830618 035 $a(CKB)2550000000058166 035 $a(EBL)861981 035 $a(OCoLC)772077899 035 $a(SSID)ssj0000571267 035 $a(PQKBManifestationID)12199143 035 $a(PQKBTitleCode)TC0000571267 035 $a(PQKBWorkID)10618252 035 $a(PQKB)11482513 035 $a(MiAaPQ)EBC861981 035 $a(Au-PeEL)EBL861981 035 $a(CaPaEBR)ebr10506623 035 $a(CaONFJC)MIL329349 035 $a(Perlego)1302074 035 $a(EXLCZ)992550000000058166 100 $a20111205d2011 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSelf assessment in musculoskeletal pathology x-rays /$fKaren Sakthivel-Wainford 205 $a1st ed. 210 $aKeswick, Cumbria $cM&K Pub.$d2011 215 $a1 online resource (291 p.) 225 1 $aX-ray interpretation, 4 300 $aDescription based upon print version of record. 311 08$a9781905539611 311 08$a1905539614 320 $aIncludes bibliographical references and index. 327 $aCover; Prelims; Contents; List of figures and tables; Acknowledgements; Introduction; Chapter 1 Arthritis; Chapter 2 Osteoporosis; Chapter 3 Bone Tumours; Chapter 4 Avascular Necrosis and the Osteochondroses; Chapter 5 Arthropathies; Chapter 6 Tumours; Chapter 7 Metabolic Bone Disease; Chapter 8 Miscellaneous Cases; Chapter 9 Mixed Cases; Reading List and Bibliography; Index 330 $aToday many radiographers are trained to report on trauma radiographs. Universities are also training student radiographers to comment on trauma radiographs. It is useful, in some cases essential, that whilst we review the trauma radiograph we also recognise and note any appropriate pathology. For instance a patient attends Accident and Emergency with pain in their knee for several weeks following trauma; the radiographs show no fracture but some signs of a malignant bony tumour, which on further investigation is an osteo sarcoma. As with the other books in the series, this book starts with sev 410 0$aX-ray interpretation, 4 606 $aX-rays 606 $aMusculoskeletal system 615 0$aX-rays. 615 0$aMusculoskeletal system. 676 $a616.7075 700 $aSakthivel-Wainford$b Karen$01805619 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910974448603321 996 $aSelf assessment in musculoskeletal pathology x-rays$94354325 997 $aUNINA LEADER 02722nam 22003853a 450 001 9910832948903321 005 20250123132213.0 035 $a(CKB)4950000000290328 035 $a(ScCtBLL)f46462dd-0fe1-4c66-b80d-9504aa1a7200 035 $a(OCoLC)1000326275 035 $a(EXLCZ)994950000000290328 100 $a20250123i20162016 uu 101 0 $aeng 135 $auru|||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aOpenIntro Statistics, 3rd Edition$fDavid M. Diez, Christopher D. Barr, Mine C?etinkaya-Rundel 205 $a3 ed. 210 1$a[s.l.] :$c[s.n.],$d2016. 215 $a1 online resource (436 p.) 330 $aAs the authors write in the preface, "Data is messy, and statistical tools are imperfect. But, when you understand the strengths and weaknesses of these tools, you can use them to learn about the real world." This book is full of examples and exercises on topics of current interest pulled from the popular media and published research.In addition to the exercises at the end of each chapter, a novel feature is the incorporation of in-chapter exercises, meant to be done immediately, with answers below in the footnotes.Chapter SummariesIntroduction to data. Data structures, variables, summaries, graphics, and basic data collection techniques.Probability. The basic principles of probability. An understanding of this chapter is not required for the main content in Chapters 3-8.Distributions of random variables. Introduction to the normal model and other key distributions.Foundations for inference. General ideas for statistical inference in the context of estimating the population mean.Inference for numerical data. Inference for one or two sample means using the normal model and t distribution, and also comparisons of many means using ANOVA.Inference for categorical data. Inference for proportions using the normal and chi-square distributions, as well as simulation and randomization techniques.Introduction to linear regression. An introduction to regression with two variables. Most of this chapter could be covered after Chapter 1.Multiple and logistic regression. An introduction to multiple regression and logistic regression for an accelerated course. 606 $aMathematics / Probability & Statistics$2bisacsh 606 $aMathematics 615 7$aMathematics / Probability & Statistics 615 0$aMathematics. 700 $aDiez$b David M$01787009 702 $aBarr$b Christopher D 702 $aC?etinkaya-Rundel$b Mine 801 0$bScCtBLL 801 1$bScCtBLL 906 $aBOOK 912 $a9910832948903321 996 $aOpenIntro Statistics, 3rd Edition$94319607 997 $aUNINA