LEADER 02494nam 22005653u 450 001 9910450620203321 005 20210117141604.0 010 $a1-84243-919-7 035 $a(CKB)1000000000006033 035 $a(EBL)895514 035 $a(OCoLC)793510923 035 $a(SSID)ssj0000282799 035 $a(PQKBManifestationID)12097838 035 $a(PQKBTitleCode)TC0000282799 035 $a(PQKBWorkID)10323349 035 $a(PQKB)11609943 035 $a(SSID)ssj0001509458 035 $a(PQKBManifestationID)11782687 035 $a(PQKBTitleCode)TC0001509458 035 $a(PQKBWorkID)11514307 035 $a(PQKB)11784258 035 $a(MiAaPQ)EBC895514 035 $a(MiAaPQ)EBC3386007 035 $a(Au-PeEL)EBL895514 035 $a(EXLCZ)991000000000006033 100 $a20130418d2012|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPhilip K. Dick$b[electronic resource] 210 $aNew York $cOldcastle Books$d2012 215 $a1 online resource (149 p.) 300 $aDescription based upon print version of record. 311 $a1-903047-29-3 327 $aCover; Title Page; Acknowledgement; Contents; 1. Philip K. Dick: Beyond the Veil; 2. Learning the Ropes 1941-1953; 3. A Double Life 1954-1960; 4. At the Peak 1961-1969; 5. Over the Edge? 1970-1982; 6. Selected Short Fiction; 7. Non-Fiction; 8. Collaborations; 9. Reference Materials; Copyright 330 $aWho was Dick? A freaked-out junkie who took too many drugs? An explorer of madness who go too close to his subject and ended up claiming to have met God? A practical joker? The most consistently brilliant SF writer in the world? At a time when most SF was about cowboys in outer space, Dick explored the landscapes of the mind, conjured fake realities and was able to make you believe six impossible things before breakfast. He embodied the counter-culture a decade before the 1960's. Perhaps best known for Do Androids Dream Of Electric Sheep? - the novel which inspired Blade Runner - Dick's 606 $aDick, Philip K. -- Criticism and interpretation 608 $aElectronic books. 615 4$aDick, Philip K. -- Criticism and interpretation. 676 $a813.54 700 $aButler$b Andrew M$0863418 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910450620203321 996 $aPhilip K. Dick$92455326 997 $aUNINA LEADER 05501nam 2200709 a 450 001 9910139034503321 005 20180928022904.0 010 $a1-118-75751-3 010 $a1-118-75433-6 010 $a1-118-75409-3 035 $a(CKB)2550000001111883 035 $a(EBL)1354330 035 $a(OCoLC)856625823 035 $a(SSID)ssj0000981519 035 $a(PQKBManifestationID)11618482 035 $a(PQKBTitleCode)TC0000981519 035 $a(PQKBWorkID)10973860 035 $a(PQKB)11579562 035 $a(MiAaPQ)EBC1354330 035 $a(DLC) 2013021083 035 $a(CaSebORM)9781118438053 035 $a(EXLCZ)992550000001111883 100 $a20130513d2013 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDecoding the IT value problem$b[electronic resource] $ean executive guide for achieving optimal ROI on critical IT investments /$fGregory J. Fell 205 $a1st edition 210 $aHoboken, N.J. $cWiley$d2013 215 $a1 online resource (204 p.) 225 0 $aWiley CIO 225 0$aWiley CIO series 300 $aDescription based upon print version of record. 311 $a1-118-43805-1 311 $a1-299-80524-8 320 $aIncludes bibliographical references and index. 327 $aDecoding the IT Value Problem; Contents; Foreword: Uncovering an Essential Skill of IT Management; Preface; Acknowledgments; Introduction; Chapter 1 The Value of IT; The 80/20 Law of IT Spending; The User Interface Is Not the Project; Just Like Buying a Car; Don't Forget Maintenance Costs; The Math of Availability; My Favorite Analogy; The Hard Facts of Uptime; Chapter 2 Why IT Projects Fail; Technology Is Not the Problem; Communication Is Critical; IT Projects Are Really Business Process Change Projects; When You Change a Process, Don't Forget the People; Paradigm Shifts Are Real 327 $aChapter 3 The Washington Principle The Skills of a Leader; Why We Need IT Governance; A Process for Generating Commitment; They Cannot Read Your Mind; Multiple Levels of Governance; Delivering Expected Value; The Basics of Good Governance; Chapter 4 Balancing Risk and Exposure; The CIA Model of Risk Assessment; An Easy Method for Modeling Risk; The Risk Profile Matrix; Bring Options and Recommendations to the Table; Managing IT Security Risks; What about the Black Swan?; Note; Chapter 5 Time Is the Enemy; Riding to Nowhere?; It's All about Time; If Necessary, Rebaseline the Project; The 5 Whys 327 $aChapter 6 Software Is Not Manufactured The Art of Programming; Consider Agile or Lean Methodologies; Chapter 7 Technology Disruptors; Keep Your Eyes on the Horizon; Think Like a VC; When Technology Disruption Hits Close to Home; Specific Trends to Watch; Beyond the Keyboard and Screen; Encourage Exploration, Experimentation, and Fast Failure; Chapter 8 The Office of Know; Correcting a Classic Case of Misalignment; Are CIOs Wired Differently?; Sometimes There's a Good Reason for Being Risk Averse; Technology Is Not the Only Solution; The View from the Crow's Nest 327 $aMoore's Law and the Cost of IT And the Moral of the Story Is . . .; Some IT Projects Are Very Expensive; Chapter 12 The CFO's Perspective; Cash, Risk, and Benefits; Chapter 13 Optimizing the CEO-CIO Relationship; Making a Strategic Contribution; The CIO Evolution; Chapter 14 Conclusions; Don't Burn Your Money; Note; Recommended Reading; About the Author; Index 330 $a"Gain greater returns from your IT investmentsRevealing the secrets to proven, effective strategies that enable businesses to leverage the full value of highly expensive IT investments, Decoding the IT Value Problem is a no-nonsense guide for making smart IT investments and cutting through the noise of vendor marketing and media hype. Author Gregory Fell describes in rich detail the actual processes, frameworks, infrastructure and discipline required to develop and execute corporate IT strategies that areprofitable and sustainable. Provides a proven framework for developing and successfully executing profitable IT strategies Plain English guidance for gaining the most return on investment from critical IT investments Explores developing and executing IT strategy; forecasting, calculating and managing IT costs; leveraging IT investments to drive business growth; IT and the evolving global economy; IT value management; communicating IT value across the enterprise; and leading change, transformation and innovation If you're a senior level manager or executive responsible for managing IT value in your business, Decoding the IT Value Problem is the practical and clearly written guide you'll turn to, with tools and tips for smart investment and management of IT costs"--$cProvided by publisher. 410 0$aWiley CIO 606 $aInformation technology 606 $aInformation technology$xCost effectiveness 606 $aCapital investments$xEvaluation 608 $aElectronic books. 615 0$aInformation technology. 615 0$aInformation technology$xCost effectiveness. 615 0$aCapital investments$xEvaluation. 676 $a004.068 676 $a004.0681 686 $aBUS063000$2bisacsh 700 $aFell$b Gregory J.$f1964-$0855865 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139034503321 996 $aDecoding the IT value problem$91910722 997 $aUNINA LEADER 01075nam a2200265 a 4500 001 991003748199707536 008 080625s2002 it 000 0 ita d 020 $a888837521X 035 $ab13745724-39ule_inst 040 $aDip.to Lingue$bita 245 00$aDiaspore europee & lettere migranti :$bprimo Festival europeo degli scrittori migranti, Roma, giugno 2002 /$c[a cura di] Armando Gnisci, Nora Moll 260 $aRoma :$bEdizioni Interculturali,$c2002 300 $a219 p. ;$c21 cm 440 0$aKúmá Lettere Migranti ;$vv. 1 650 4$aAutori immigrati$vCongressi 650 4$aScrittori immigrati$vCongressi 650 4$aLetteratura moderna$ySec. 20$xStoria e critica$vCongressi 700 1 $aGnisci, Armando 700 1 $aMoll, Nora 907 $a.b13745724$b02-04-14$c25-06-08 912 $a991003748199707536 945 $aLE012 809 GNI 2$g1$i2012000347007$lle012$o-$pE0.00$q-$rl$s- $t0$u7$v3$w7$x0$y.i1478418x$z25-06-08 996 $aDiaspore europee & lettere migranti$91226436 997 $aUNISALENTO 998 $ale012$b25-06-08$cm$da $e-$fita$git $h0$i0 LEADER 05543nam 2200685 a 450 001 9910830897103321 005 20170815111120.0 010 $a1-281-84100-5 010 $a9786611841003 010 $a0-470-77077-5 010 $a0-470-77078-3 035 $a(CKB)1000000000549390 035 $a(EBL)366774 035 $a(OCoLC)476201818 035 $a(SSID)ssj0000206842 035 $a(PQKBManifestationID)11180050 035 $a(PQKBTitleCode)TC0000206842 035 $a(PQKBWorkID)10246504 035 $a(PQKB)10229985 035 $a(MiAaPQ)EBC366774 035 $a(PPN)263348644 035 $a(EXLCZ)991000000000549390 100 $a20080124d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMultivariable model-building$b[electronic resource] $ea pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables /$fPatrick Royston, Willi Sauerbrei 210 $aChichester, England ;$aHoboken, NJ $cJohn Wiley$dc2008 215 $a1 online resource (323 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 $a0-470-02842-4 320 $aIncludes bibliographical references (p. 271-283) and index. 327 $aMultivariable Model-Building; Contents; Preface; 1 Introduction; 1.1 Real-Life Problems as Motivation for Model Building; 1.1.1 Many Candidate Models; 1.1.2 Functional Form for Continuous Predictors; 1.1.3 Example 1: Continuous Response; 1.1.4 Example 2: Multivariable Model for Survival Data; 1.2 Issues in Modelling Continuous Predictors; 1.2.1 Effects of Assumptions; 1.2.2 Global versus Local Influence Models; 1.2.3 Disadvantages of Fractional Polynomial Modelling; 1.2.4 Controlling Model Complexity; 1.3 Types of Regression Model Considered; 1.3.1 Normal-Errors Regression 327 $a1.3.2 Logistic Regression1.3.3 Cox Regression; 1.3.4 Generalized Linear Models; 1.3.5 Linear and Additive Predictors; 1.4 Role of Residuals; 1.4.1 Uses of Residuals; 1.4.2 Graphical Analysis of Residuals; 1.5 Role of Subject-Matter Knowledge in Model Development; 1.6 Scope of Model Building in our Book; 1.7 Modelling Preferences; 1.7.1 General Issues; 1.7.2 Criteria for a Good Model; 1.7.3 Personal Preferences; 1.8 General Notation; 2 Selection of Variables; 2.1 Introduction; 2.2 Background; 2.3 Preliminaries for a Multivariable Analysis; 2.4 Aims of Multivariable Models 327 $a2.5 Prediction: Summary Statistics and Comparisons2.6 Procedures for Selecting Variables; 2.6.1 Strength of Predictors; 2.6.2 Stepwise Procedures; 2.6.3 All-Subsets Model Selection Using Information Criteria; 2.6.4 Further Considerations; 2.7 Comparison of Selection Strategies in Examples; 2.7.1 Myeloma Study; 2.7.2 Educational Body-Fat Data; 2.7.3 Glioma Study; 2.8 Selection and Shrinkage; 2.8.1 Selection Bias; 2.8.2 Simulation Study; 2.8.3 Shrinkage to Correct for Selection Bias; 2.8.4 Post-estimation Shrinkage; 2.8.5 Reducing Selection Bias; 2.8.6 Example; 2.9 Discussion 327 $a2.9.1 Model Building in Small Datasets2.9.2 Full, Pre-specified or Selected Model?; 2.9.3 Comparison of Selection Procedures; 2.9.4 Complexity, Stability and Interpretability; 2.9.5 Conclusions and Outlook; 3 Handling Categorical and Continuous Predictors; 3.1 Introduction; 3.2 Types of Predictor; 3.2.1 Binary; 3.2.2 Nominal; 3.2.3 Ordinal, Counting, Continuous; 3.2.4 Derived; 3.3 Handling Ordinal Predictors; 3.3.1 Coding Schemes; 3.3.2 Effect of Coding Schemes on Variable Selection; 3.4 Handling Counting and Continuous Predictors: Categorization 327 $a3.4.1 'Optimal' Cutpoints: A Dangerous Analysis3.4.2 Other Ways of Choosing a Cutpoint; 3.5 Example: Issues in Model Building with Categorized Variables; 3.5.1 One Ordinal Variable; 3.5.2 Several Ordinal Variables; 3.6 Handling Counting and Continuous Predictors: Functional Form; 3.6.1 Beyond Linearity; 3.6.2 Does Nonlinearity Matter?; 3.6.3 Simple versus Complex Functions; 3.6.4 Interpretability and Transportability; 3.7 Empirical Curve Fitting; 3.7.1 General Approaches to Smoothing; 3.7.2 Critique of Local and Global Influence Models; 3.8 Discussion; 3.8.1 Sparse Categories 327 $a3.8.2 Choice of Coding Scheme 330 $aMultivariable regression models are of fundamental importance in all areas of science in which empirical data must be analyzed. This book proposes a systematic approach to building such models based on standard principles of statistical modeling. The main emphasis is on the fractional polynomial method for modeling the influence of continuous variables in a multivariable context, a topic for which there is no standard approach. Existing options range from very simple step functions to highly complex adaptive methods such as multivariate splines with many knots and penalisation. This new approa 410 0$aWiley series in probability and statistics. 606 $aRegression analysis 606 $aPolynomials 606 $aVariables (Mathematics) 615 0$aRegression analysis. 615 0$aPolynomials. 615 0$aVariables (Mathematics) 676 $a519.5 676 $a519.536 700 $aRoyston$b Patrick$01341128 701 $aSauerbrei$b Willi$01649001 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830897103321 996 $aMultivariable model-building$93997498 997 $aUNINA