“…Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on plain text, CSV, HTML/XML, and JSON Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow using Drake Create reusable tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines using GNU Parallel Model data with dimensionality reduction, clustering, regression, and classification algorithms…”

“…DB2 PE simplifies DB2 performance management by providing you with the ability to monitor applications, system statistics, and system parameters using a single tool. …”

“…Thomas Fleming, professor of biostatistics and statistics at the University of Washington, gave a keynote presentation on the critical issues in the validation of surrogate endpoints, a specific use of a biomarker. …”

“…A number of sources of surveillance data--including population surveys, cohort studies, disease registries, administrative health data, and vital statistics--contribute critical information about chronic disease. …”

“…Narratives are more powerful than raw statistics, more enduring than pretty charts. When done correctly, data stories can influence decisions and drive change. …”

“…Subsequent chapters provide extensive data and statistics, while the closing section showcases photos from all periods of the Union’s history. …”

“…Over half of OECD countries require private sector firms to report their gender pay gap statistics regularly to stakeholders like employees, employee representatives, the government, and/or the public. …”

“…It also covers the HR skills needed to ensure professional success, including leadership, managing conflict, interviewing and using statistics. It is illustrated throughout in full colour and has a range of pedagogical features to consolidate learning such as source review boxes, key learning points and case studies from international organizations such as IBM, HSBC and Johnson and Johnson. …”

“…It combines theory and method from multiple disciples (psychology, economics, statistics, decision theory, management science). It employs both empirical methods, to study how decisions are actually made, and analytical ones, to study how decisions should be made and how consequential imperfections are. …”

“…Generously illustrated with photographs, visual data, and statistics, and featuring a series of essays written by leading people in their fields, Shaping Cities in an Urban Age addresses our most urgent contemporary and future urban issues by examining a set of key forces that have combined to create the city as we know it today."-- Publisher's website…”

Tabla de Contenidos: “…6.1.2 - Semivariogram in random intercept linear models -- 6.1.3 - Semivariogram in the linear random coefficient model -- 6.2 - Influence diagnostics -- 6.2.1 - Cook's D and related influence diagnostics -- 6.2.2 - Leverage -- 6.2.3 - DFFITS, MDFFITS, COVTRACE, and COVRATIO statistics -- 6.2.4 - Likelihood displacement statistic approximation -- 6.2.5 - LMAX statistic for identification of influential observations -- 6.3 - Empirical illustrations on influence diagnostics -- 6.3.1 - Influence checks on linear mixed model concerning effectiveness of acupuncture treatment on PCL score -- 6.3.2 - Influence diagnostics on linear mixed model concerning marital status and disability severity among older Americans -- 6.4 - Summary -- Chapter 7 - Special topics on linear mixed models -- 7.1 - Adjustment of baseline response in longitudinal data analysis -- 7.1.1 - Adjustment of baseline score and the Lord's paradox -- 7.1.2 - Adjustment of baseline score in longitudinal data analysis -- 7.1.3 - Empirical illustrations on adjustment of baseline score -- 7.2 - Misspecification of the assumed distribution of random effects -- 7.2.1 - Heterogeneity linear mixed model -- 7.2.2 - Nonnormal random effect distribution in linear mixed models -- 7.2.3 - Best predicted random effects in different distributions -- 7.2.4 - Empirical illustration: comparison between BLUP and least squares means -- 7.3 - Pattern-mixture modeling -- 7.3.1 - Classification of heterogeneous groups -- 7.3.2 - Basic theory of pattern-mixture modeling -- 7.3.3 - Pattern-mixture model -- 7.3.4 - Empirical illustration of pattern-mixture modeling -- 7.4 - Summary -- Chapter 8 - Generalized linear mixed models on nonlinear longitudinal data -- 8.1 - A brief overview of generalized linear models -- 8.2 - Generalized linear mixed models and statistical inferences…”

Tabla de Contenidos: “…Chapter 7 Data-Based Mechanistic Modelling and the Emulation of Large Environmental System Models7.1 Introduction; 7.2 Philosophies of science and modelling; 7.3 Statistical identification, estimation and validation; 7.4 Data-based mechanistic (DBM) modelling; 7.5 The statistical tools of DBM modelling; 7.6 Practical example; 7.7 The reduced-order modelling of large computer-simulation models; 7.8 The dynamic emulation of large computer-simulation models; 7.9 Conclusions; References; Chapter 8 Stochastic versus Deterministic Approaches; 8.1 Introduction; 8.2 A philosophical perspective…”

Tabla de Contenidos: “…Ordinary least squares for nonlinear models (Beck and Arnold, 2007); 2.3.1.3. Statistics for the parameters…”

Tabla de Contenidos: “…-- 1.5 Randomness and Providence -- 1.6 Conclusion -- Bibliography -- Part II: The Problem(s) Stated -- Chapter 2: The Many Faces of Randomness -- 2.1 No Single Definition -- 2.2 Purpose -- 2.3 Probability and Statistics -- 2.4 Physics -- 2.4.1 Statistical Mechanics -- 2.4.2 Chaos Theory -- 2.4.3 Instability and Singular Points…”

Tabla de Contenidos: “…2.3 Theoretical Properties of Univariate EVT-Block Maxima and the GEV Family2.4 Generalized Extreme Value Loss Distributional Approach (GEV-LDA); 2.4.1 Statistical Considerations for Applicability of the GEV Model; 2.4.2 Various Statistical Estimation Procedures for the GEV Model Parameters in OpRisk Settings; 2.4.3 GEV Sub-Family Approaches in OpRisk LDA Modeling; 2.4.4 Properties of the Frechet-Pareto Family of Severity Models; 2.4.5 Single Risk LDA Poisson-Generalized Pareto Family; 2.4.6 Single Risk LDA Poisson-Burr Family; 2.4.7 Properties of the Gumbel family of Severity Models…”

Tabla de Contenidos: “…Histograms""; ""2.9 Statistical Errors and Arrow Graphics""; ""Chapter 3: Three-Dimensional Graphics, Warped Curves and Surfaces, Contour Graphics""…”

Tabla de Contenidos: “…Ranges and Outliers; 4.2. Simple Statistical Descriptors; 4.3. Retrieving Image Information; 4.4. …”

Tabla de Contenidos: “…Tools for performance monitoringUsing esxtop/resxtop; Live resource monitoring - the interactive mode; Offline performance monitoring - batch mode; Replaying performance metrics - replay mode; Using Windows Performance Monitor; Analyzing esxtop results; Understanding CPU statistics; Enabling more esxtop fields; Memory statistics; Memory management in a vSphere host; Memory overcommitment; Memory overhead; Transparent page sharing; Ballooning; Memory compression; Diagnosing memory blockage; Network metrics; Understanding network metrics; Diagnosing network performance; Storage metrics…”

Tabla de Contenidos: “…Overview of Institutional Contexts, Empirical Methods; 3.1 Introduction and Learning Objectives; 3.2 An Overview of the International Institutional and Legal Context; 3.3 Statistics and Econometrics Used in This Book; 3.4 Summary; Key Terms; Key Statistical and Econometric Terms; Discussion Questions; Part Two: Fund Structure and Governance; Chapter 4. …”

Tabla de Contenidos: “…Chapter 3.12 Local and Global Stereo MethodsChapter 3.13 Image Sequence Stabilization, Mosaicking, and Superresolution; Section IV: Image and Video Analysis; Image Representations and Image Models; Chapter 4.1 Computational Models of Early Human Vision; Chapter 4.2 Multiscale Image Decompositions and Wavelets; Chapter 4.3 Random Field Models; Chapter 4.4 AM-FM Image Models: Fundamental Techniques and Emerging Trends; Chapter 4.5 Image Noise Models; Chapter 4.6 Color and Multispectral Image Representation and Display; Chapter 4.7 Statistical Modeling of Photographic Images…”