LEADER 01501nam0 2200349 i 450 001 SUN0124455 005 20191021090403.347 010 $d0.00 017 70$2N$a978-88-7642-638-4 100 $a20191018d2018 |0engc50 ba 101 $aeng 102 $aIT 105 $a|||| ||||| 200 1 $a*Interpolation Theory$fAlessandra Lunardi 205 $a3. ed 210 $aPisa$cEdizioni della Normale$d2018 215 $axiv, 199 p.$d24 cm 410 1$1001SUN0123760$12001 $a*Lecture notes$v16$1210 $aPisa$cScuola Normale Superiore. 606 $a46-XX$xFunctional analysis [MSC 2020]$2MF$3SUNC019764 606 $a47D06$xOne-parameter semigroups and linear evolution equations [MSC 2020]$2MF$3SUNC020305 606 $a47Fxx$xPartial differential operators [MSC 2020]$2MF$3SUNC022222 606 $a46B70$xInterpolation between normed linear spaces [MSC 2020]$2MF$3SUNC023216 606 $a46M35$xAbstract interpolation of topological vector spaces [MSC 2020]$2MF$3SUNC024763 620 $dPisa$3SUNL000008 700 1$aLunardi$b, Alessandra$3SUNV043045$061555 712 $aScuola normale superiore di Pisa$3SUNV001558$4650 801 $aIT$bSOL$c20210503$gRICA 856 4 $uhttp://doi.org/10.1007/978-88-7642-638-4 912 $aSUN0124455 950 $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 1199 $e08eMF1199 20191018 996 $aInterpolation theory$9233458 997 $aUNICAMPANIA LEADER 05159nam 22006614a 450 001 9910830689103321 005 20230617031142.0 010 $a1-280-36626-5 010 $a9786610366262 010 $a0-470-31811-2 010 $a0-471-45865-1 010 $a0-471-45871-6 035 $a(CKB)1000000000019028 035 $a(EBL)468893 035 $a(OCoLC)609847619 035 $a(SSID)ssj0000300435 035 $a(PQKBManifestationID)11232936 035 $a(PQKBTitleCode)TC0000300435 035 $a(PQKBWorkID)10251094 035 $a(PQKB)11331727 035 $a(MiAaPQ)EBC468893 035 $a(EXLCZ)991000000000019028 100 $a20021021d2003 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIntroductory biostatistics for the health sciences$b[electronic resource] $emodern applications including bootstrap /$fMichael R. Chernick and Robert H. Friis 210 $aHoboken, N.J. $cWiley-Interscience$dc2003 215 $a1 online resource (426 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 $a0-471-41137-X 320 $aIncludes bibliographical references and index. 327 $aIntroductory Biostatistics for the Health Sciences; Contents; Preface; 1. What is Statistics? How is it Applied in the Health Sciences?; 1.1 Definitions of Statistics and Statisticians; 1.2 Why Study Statistics?; 1.3 Types of Studies; 1.3.1 Surveys and Cross-Sectional Studies; 1.3.2 Retrospective Studies; 1.3.3 Prospective Studies; 1.3.4 Experimental Studies and Quality Control; 1.3.5 Clinical Trials; 1.3.6 Epidemiological Studies; 1.3.7 Pharmacoeconomic Studies and Quality of Life; 1.4 Exercises; 1.5 Additional Reading; 2. Defining Populations and Selecting Samples 327 $a2.1 What are Populations and Samples?2.2 Why Select a Sample?; 2.3 How Samples Can be Selected; 2.3.1 Simple Random Sampling; 2.3.2 Convenience Sampling; 2.3.3 Systematic Sampling; 2.3.4 Stratified Random Sampling; 2.3.5 Cluster Sampling; 2.3.6 Bootstrap Sampling; 2.4 How to Select a Simple Random Sample; 2.5 How to Select a Bootstrap Sample; 2.6 Why Does Random Sampling Work?; 2.7 Exercises; 2.8 Additional Reading; 3. Systematic Organization and Display of Data; 3.1 Types of Data; 3.1.1 Qualitative; 3.1.2 Quantitative; 3.2 Frequency Tables and Histograms; 3.3 Graphical Methods 327 $a3.3.1 Frequency Histograms3.3.2 Frequency Polygons; 3.3.3 Cumulative Frequency Polygon; 3.3.4 Stem-and-Leaf Diagrams; 3.3.5 Box-and-Whisker Plots; 3.3.6 Bar Charts and Pie Charts; 3.4 Exercises; 3.5 Additional Reading; 4. Summary Statistics; 4.1 Measures of Central Tendency; 4.1.1 The Arithmetic Mean; 4.1.2 The Median; 4.1.3 The Mode; 4.1.4 The Geometric Mean; 4.1.5 The Harmonic Mean; 4.1.6 Which Measure Should You Use?; 4.2 Measures of Dispersion; 4.2.1 Range; 4.2.2 Mean Absolute Deviation; 4.2.3 Population Variance and Standard Deviation; 4.2.4 Sample Variance and Standard Deviation 327 $a4.2.5 Calculating the Variance and Standard Deviation from Group Data4.3 Coefficient of Variation (CV) and Coefficient of Dispersion (CD); 4.4 Exercises; 4.5 Additional Reading; 5. Basic Probability; 5.1 What is Probability?; 5.2 Elementary Sets as Events and Their Complements; 5.3 Independent and Disjoint Events; 5.4 Probability Rules; 5.5 Permutations and Combinations; 5.6 Probability Distributions; 5.7 The Binomial Distribution; 5.8 The Monty Hall Problem; 5.9 A Quality Assurance Problem; 5.10 Exercises; 5.11 Additional Reading; 6. The Normal Distribution 327 $a6.1 The Importance of the Normal Distribution in Statistics6.2 Properties of Normal Distributions; 6.3 Tabulating Areas under the Standard Normal Distribution; 6.4 Exercises; 6.5 Additional Reading; 7. Sampling Distributions for Means; 7.1 Population Distributions and the Distribution of Sample Averages from the Population; 7.2 The Central Limit Theorem; 7.3 Standard Error of the Mean; 7.4 Z Distribution Obtained When Standard Deviation Is Known; 7.5 Student's t Distribution Obtained When Standard Deviation Is Unknown; 7.6 Assumptions Required for t Distribution; 7.7 Exercises 327 $a7.8 Additional Reading 330 $aAccessible to medicine- and/or public policy-related audiences, as well as most statisticians.Emphasis on outliers is discussed by way of detection and treatment.Resampling statistics software is incorporated throughout.Motivating applications are presented in light of honest theory.Plentiful exercises are sprinkled throughout. 410 0$aWiley series in probability and statistics. 606 $aMedical statistics 606 $aBiometry 615 0$aMedical statistics. 615 0$aBiometry. 676 $a519.502461 676 $a610.72 700 $aChernick$b Michael R$0140081 701 $aFriis$b Robert H$01603121 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830689103321 996 $aIntroductory biostatistics for the health sciences$93927375 997 $aUNINA