LEADER 00997nam0-2200289 --450 001 9910283159803321 005 20180903101243.0 010 $a978-88-227-0085-8 100 $a20180903d2017----kmuy0itay5050 ba 101 0 $aita 102 $aIT 105 $a 001yy 200 1 $a<>grandi battaglie della seconda guerra mondiale$edal fronte italiano alla Russia, da Pearl Harbor allo sbarco in Normandia, tutti gli scontri decisivi dell'ultimo conflitto$fGiuseppe Rasolo 205 $aNuova ed. 210 $aRoma$cNewton Compton$d2017 215 $a425 p.$cill.$d24 cm 225 1 $a<>volti della storia$v394 610 0 $aGuerra mondiale$a1939-1945$aBattaglie 676 $a940.542$v23$zita 700 1$aRasolo,$bGiuseppe$f<1966->$0750745 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910283159803321 952 $aXIV B 2691$b1300/2018$fFSPBC 959 $aFSPBC 996 $aGrandi battaglie della seconda guerra mondiale$91510190 997 $aUNINA LEADER 05527nam 2200733Ia 450 001 9911018789803321 005 20200520144314.0 010 $a9786610253319 010 $a9781280253317 010 $a1280253312 010 $a9780470248058 010 $a047024805X 010 $a9780471726111 010 $a0471726117 010 $a9780471728412 010 $a0471728411 035 $a(CKB)1000000000018992 035 $a(EBL)226443 035 $a(SSID)ssj0000251094 035 $a(PQKBManifestationID)11227623 035 $a(PQKBTitleCode)TC0000251094 035 $a(PQKBWorkID)10248229 035 $a(PQKB)10729694 035 $a(MiAaPQ)EBC226443 035 $a(OCoLC)777630157 035 $a(Perlego)2776498 035 $a(EXLCZ)991000000000018992 100 $a19990309d2000 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical methods in analytical chemistry /$fPeter C. Meier, Richard E. Zund 205 $a2nd ed. 210 $aNew York $cWiley$dc2000 215 $a1 online resource (452 p.) 225 1 $aChemical analysis ;$vv. 153 300 $a"A Wiley-Interscience publication." 311 08$a9780471293637 311 08$a0471293636 320 $aIncludes bibliographical references (p. 404-415) and index. 327 $aStatistical Methods in Analytical Chemistry; CHEMICAL ANALYSIS; CONTENTS; PREFACE; CHEMICAL ANALYSIS SERIES; INTRODUCTION; CHAPTER 1: UNIVARIATE DATA; 1.1 Mean and Standard Deviation; 1.1.1 The Most Probable Value; 1.1.2 The Dispersion; 1.1.3 Independency of Measurements; 1.1.4 Reproducibility and Repeatibility; 1.1.5 Reporting the Results; 1.1.6 Interpreting the Results; 1.2 Distributions and the Problem of Small Numbers; 1.2.1 The Normal Distribution; 1.2.2 Student's t Distribution; 1.3 Confidence Limits; 1.3.1 Confidence Limits of the Distribution; 1.3.2 Confidence Limits of the Mean 327 $a1.4 The Simulation of a Series of Measurements1.5 Testing for Deviations; 1.5.1 Examining Two Series of Measurements; 1.5.2 The t-Test; 1.5.3 Extension of the t-Test to More Than Two Series of Measurements; 1.5.4 Multiple-Range Test; 1.5.5 Outlier Tests; 1.5.6 Analysis of Variance (ANOVA); 1.6 Number of Determinations; 1.7 Width of a Distribution; 1.7.1 The F-Test; 1.7.2 Confidence Limits for a Standard Deviation; 1.7.3 Bartlett Test; 1.8 Charting a Distribution; 1.8.1 Histograms; 1.8.2 X2-Test; 1.8.3 Probability Charts; 1.8.4 Conventional Control Charts (Shewhart Charts); 1.8.5 Cumsum Charts 327 $a1.9 Errors of the First and Second KindCHAPTER 2: BI- AND MULTIVARIATE DATA; 2.1 Correlation; 2.2 Linear Regression; 2.2.1 The Standard Approach; 2.2.2 Slope and Intercept; 2.2.3 Residual Variance; 2.2.4 Testing Linearity and Slope; 2.2.5 Interpolating Y(x); 2.2.6 Interpolating X(y); 2.2.7 Limit of Detection; 2.2.8 Minimizing the Costs of a Calibration; 2.2.9 Standard Addition; 2.2.10 Weighted Regression; 2.2.11 The Intersection of Two Linear Regression Lines; 2.3 Nonlinear Regression; 2.3.1 Linearization; 2.3.2 Nonlinear Regression and Modeling; 2.4 Multidimensional Data/Visualizing Data 327 $aCHAPTER 3: RELATED TOPICS3.1 GMP Background: Selectivity and Interference/Linearity/Accuracy/Precision/Reliability/Economic Considerations; 3.2 Development, Qualification, and Validation; Installation Qualification, Operations Qualification, Performance Qualification/Method Development/Method Validation; 3.3 Data Treatment Scheme: Data Acquisition/Acceptance Criteria/Data Assembly and Clean-up/Data Evaluation/ Presentation of R; 3.4 Exploratory Data Analysis (EDA); 3.5 Optimization Techniques; 3.5.1 Full Factorial vs. Classical Experiments; 3.5.2 Simplex-Guided Experiments 327 $a3.5.3 Optimization of the Model: Curve Fitting3.5.4 Computer Simulation; 3.5.5 Monte Carlo Technique (MCT); 3.6 Smoothing and Filtering Data/Box-Car Averaging/Moving Average/Savitzky-Golay Filtering/CUSUM; 3.7 Error Propagation and Numerical Artifacts; 3.8 Programs; CHAPTER 4: COMPLEX EXAMPLES; 4.1 To Weigh or Not to Weigh; 4.2 Nonlinear Fitting; 4.3 UV-Assay Cost Structure; 4.4 Process Validation; 4.5 Regulations and Realities; 4.6 Diffusing Vapors; 4.7 Stability a la Carte; 4.8 Secret Shampoo Switch; 4.9 Tablet Press Woes; 4.10 Sounding Out Solubility; 4.11 Exploring a Data Jungle 327 $a4.12 Sifting Through Sieved Samples 330 $aThis new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly demonstrates how to obtain reliable results by choosing the most appropriate experimental design and data evaluation methods.Unlike other books on the subject, Statistical Methods in Analytical Chemistry, Second Edition presents and solves problems in the co 410 0$aChemical analysis ;$vv. 153. 606 $aChemometrics 606 $aChemistry 615 0$aChemometrics. 615 0$aChemistry. 676 $a543/.007/2 700 $aMeier$b Peter C.$f1945-$01838359 701 $aZund$b Richard E$01838360 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911018789803321 996 $aStatistical methods in analytical chemistry$94417324 997 $aUNINA