05494nam 2200721 a 450 991046466360332120200520144314.01-283-44664-297866134466400-8213-8913-0(CKB)3460000000023790(EBL)841923(OCoLC)773566707(SSID)ssj0000591998(PQKBManifestationID)12219386(PQKBTitleCode)TC0000591998(PQKBWorkID)10728669(PQKB)10996868(MiAaPQ)EBC841923(Au-PeEL)EBL841923(CaPaEBR)ebr10527217(CaONFJC)MIL344664(OCoLC)778436421(EXLCZ)99346000000002379020111013d2011 uy 0engur|n|---|||||txtccrMore and better jobs in South Asia[electronic resource] /World BankWashington, D.C. World Bank20111 online resource (356 p.)South Asia development mattersDescription based upon print version of record.0-8213-8912-2 Includes bibliographical references.Contents; Foreword; Preface; Acknowledgments; Abbreviations; 1 Overview; South Asia's track record; Determinants of job quality and the employment challenge; Improving an inconducive business environment; Improving workers' skills; Reforming labor market institutions; Creating jobs in conflict-affected areas; Conclusion; Annex 1A Summary statistics on South Asian countries; Annex 1B Definition of key labor market terms; Annex 1C What is a "better" job, and which jobs are "better"?; Notes; References; 2 Growth and Job Quality in South Asia; Economic growth in South AsiaSources of future growthThe track record on employment; The urgency of reform; Annex 2A Methodology for decomposing growth; Annex 2B Sources of average annual growth in output per worker; Annex 2C Shares of agriculture, industry, and services in employment and GDP; Annex 2D Methodology and data sources for labor force projections; Annex 2E Poverty rates and the number of working poor in South Asia; Annex 2F Analysis of poverty and unemployment in India; Notes; References; 3 A Profile of South Asia at Work; Overview of employment and labor force participation in South AsiaThe nature of employmentWhere are the better jobs?; Who holds better jobs?; Annex 3A Definitions and criteria used in Profile of South Asia at work; Annex 3B Regional employment patterns; Notes; References; 4 What Is Preventing Firms from Creating More and Better Jobs?; Methodological framework; Constraints in the urban formal sector; Constraints in the rural nonfarm and informal sectors; Demand-side policy options; Constraints facing potential firm entrants: Business entry regulations; Annex 4A Business environment constraints in high- and low-income states in IndiaAnnex 4B Tax rates as a constraint to firmsAnnex 4C Constraints facing nonbenchmark firms; Annex 4D Access to finance as a constraint to firms; Annex 4E Policy options for increasing access to finance; Notes; References; 5 Opening the Door to Better Jobs by Improving Education and Skills; Education and skills in South Asian labor markets; Education and access to better jobs; The education challenge; The next 20 years: Can South Asian countries improve the educational attainment of their labor forces?; Addressing disadvantages before school: The role of early childhood developmentPrimary and secondary educationTertiary education and preemployment training systems; On-the-job training; Annex 5A Additional tables and figures on education and skills; Annex 5B Projections of the educational attainment of South Asia's population and labor force; Notes; References; 6 The Role of Labor Market Regulations, Institutions, and Programs; Labor market institutions, policies, and programs in the formal sector; Labor market institutions, policies, and programs in the informal sector; Annex 6A Additional tables and figures on labor market regulations and institutions; NotesReferencesSouth Asia has created nearly 800,000 jobs per month during the last decade. Robust economic growth in large parts of the region has created better jobs -- those that pay higher wages for wage workers and reduce poverty for the self-employed, the largest segment of the region's employed. Going forward, South Asia faces the enormous challenge of absorbing 1 to 1.2 million entrants to the labor force every month for the next two decades at rising levels of productivity. This calls for an agenda that cuts across sectors and includes improving the reliability of electricity supply for firms in botSouth Asia development matters.Labor marketSouth AsiaLabor policySouth AsiaLabor supplySouth AsiaSouth AsiaEconomic policySouth AsiaEconomic conditionsElectronic books.Labor marketLabor policyLabor supply331.120954World Bank.MiAaPQMiAaPQMiAaPQBOOK9910464663603321More and better jobs in South Asia2481640UNINA05568nam 22006974a 450 99621165510331620230617031032.01-280-36625-797866103662550-470-30781-10-471-45864-30-471-44835-4(CKB)1000000000018977(EBL)159847(OCoLC)123112222(SSID)ssj0000295984(PQKBManifestationID)11250991(PQKBTitleCode)TC0000295984(PQKBWorkID)10322357(PQKB)10628633(MiAaPQ)EBC159847(EXLCZ)99100000000001897720021105d2003 uy 0engur|n|---|||||txtccrExploratory data mining and data cleaning[electronic resource] /Tamraparni Dasu, Theorodre JohnsonNew York Wiley-Interscience20031 online resource (226 p.)Wiley series in probability and statisticsDescription based upon print version of record.0-471-26851-8 Includes bibliographical references (p. 189-195) and index.Exploratory Data Mining and Data Cleaning; Contents; Preface; 1. Exploratory Data Mining and Data Cleaning: An Overview; 1.1 Introduction; 1.2 Cautionary Tales; 1.3 Taming the Data; 1.4 Challenges; 1.5 Methods; 1.6 EDM; 1.6.1 EDM Summaries-Parametric; 1.6.2 EDM Summaries-Nonparametric; 1.7 End-to-End Data Quality (DQ); 1.7.1 DQ in Data Preparation; 1.7.2 EDM and Data Glitches; 1.7.3 Tools for DQ; 1.7.4 End-to-End DQ: The Data Quality Continuum; 1.7.5 Measuring Data Quality; 1.8 Conclusion; 2. Exploratory Data Mining; 2.1 Introduction; 2.2 Uncertainty; 2.2.1 Annotated Bibliography2.3 EDM: Exploratory Data Mining2.4 EDM Summaries; 2.4.1 Typical Values; 2.4.2 Attribute Variation; 2.4.3 Example; 2.4.4 Attribute Relationships; 2.4.5 Annotated Bibliography; 2.5 What Makes a Summary Useful?; 2.5.1 Statistical Properties; 2.5.2 Computational Criteria; 2.5.3 Annotated Bibliography; 2.6 Data-Driven Approach-Nonparametric Analysis; 2.6.1 The Joy of Counting; 2.6.2 Empirical Cumulative Distribution Function (ECDF); 2.6.3 Univariate Histograms; 2.6.4 Annotated Bibliography; 2.7 EDM in Higher Dimensions; 2.8 Rectilinear Histograms; 2.9 Depth and Multivariate Binning2.9.1 Data Depth2.9.2 Aside: Depth-Related Topics; 2.9.3 Annotated Bibliography; 2.10 Conclusion; 3. Partitions and Piecewise Models; 3.1 Divide and Conquer; 3.1.1 Why Do We Need Partitions?; 3.1.2 Dividing Data; 3.1.3 Applications of Partition-Based EDM Summaries; 3.2 Axis-Aligned Partitions and Data Cubes; 3.2.1 Annotated Bibliography; 3.3 Nonlinear Partitions; 3.3.1 Annotated Bibliography; 3.4 DataSpheres (DS); 3.4.1 Layers; 3.4.2 Data Pyramids; 3.4.3 EDM Summaries; 3.4.4 Annotated Bibliography; 3.5 Set Comparison Using EDM Summaries; 3.5.1 Motivation; 3.5.2 Comparison Strategy3.5.3 Statistical Tests for Change3.5.4 Application-Two Case Studies; 3.5.5 Annotated Bibliography; 3.6 Discovering Complex Structure in Data with EDM Summaries; 3.6.1 Exploratory Model Fitting in Interactive Response Time; 3.6.2 Annotated Bibliography; 3.7 Piecewise Linear Regression; 3.7.1 An Application; 3.7.2 Regression Coefficients; 3.7.3 Improvement in Fit; 3.7.4 Annotated Bibliography; 3.8 One-Pass Classification; 3.8.1 Quantile-Based Prediction with Piecewise Models; 3.8.2 Simulation Study; 3.8.3 Annotated Bibliography; 3.9 Conclusion; 4. Data Quality; 4.1 Introduction4.2 The Meaning of Data Quality4.2.1 An Example; 4.2.2 Data Glitches; 4.2.3 Conventional Definition of DQ; 4.2.4 Times Have Changed; 4.2.5 Annotated Bibliography; 4.3 Updating DQ Metrics: Data Quality Continuum; 4.3.1 Data Gathering; 4.3.2 Data Delivery; 4.3.3 Data Monitoring; 4.3.4 Data Storage; 4.3.5 Data Integration; 4.3.6 Data Retrieval; 4.3.7 Data Mining/Analysis; 4.3.8 Annotated Bibliography; 4.4 The Meaning of Data Quality Revisited; 4.4.1 Data Interpretation; 4.4.2 Data Suitability; 4.4.3 Dataset Type; 4.4.4 Attribute Type; 4.4.5 Application Type4.4.6 Data Quality-A Many Splendored ThingWritten for practitioners of data mining, data cleaning and database management. Presents a technical treatment of data quality including process, metrics, tools and algorithms.Focuses on developing an evolving modeling strategy through an iterative data exploration loop and incorporation of domain knowledge.Addresses methods of detecting, quantifying and correcting data quality issues that can have a significant impact on findings and decisions, using commercially available tools as well as new algorithmic approaches.Uses case studies to illustrate applications in realWiley series in probability and statistics.Data miningElectronic data processingData preparationElectronic data processingQuality controlData mining.Electronic data processingData preparation.Electronic data processingQuality control.005.741006.3006.312Dasu Tamraparni281835Johnson Theodore281836MiAaPQMiAaPQMiAaPQBOOK996211655103316Exploratory data mining and data cleaning673537UNISA01596oam 2200409 450 991070493070332120140211084818.0(CKB)5470000002446440(OCoLC)869930148(EXLCZ)99547000000244644020140206d2012 ua 0engurcn|||||||||txtrdacontentcrdamediacrrdacarrierProviding guidance to practitioners in the analysis of benefits and costs of management and operations projects[Washington, D.C.] :U.S. Department of Transportation, Federal Highway Administration,2012.1 online resource (2 unnumbered pages) color illustrationsTitle from title screen (viewed on Feb. 6, 2014)."November 2012.""FHWA-HOP-13-004"--Page [2].FHWA operations benefit/cost analysis desk referenceTransportation agenciesUnited StatesManagementCost effectivenessTraffic engineeringUnited StatesValue analysis (Cost control)Transportation agenciesManagementCost effectiveness.Traffic engineeringValue analysis (Cost control)United States.Federal Highway Administration,GPOGPOGPOBOOK9910704930703321Providing guidance to practitioners in the analysis of benefits and costs of management and operations projects3353096UNINA