Intro; Preface; Contents; About the Editors; Advances in Survey Methods and New Sources in Public Statistics; Robustness in Survey Sampling Using the Conditional Bias Approach with R Implementation; 1 Introduction; 2 The Conditional Bias as a Measure of Influence in Survey Sampling; 3 Robust Estimators; 4 Application to Winsorized Estimators; 5 Robust Estimation of Domain Totals; 6 Implementation with the R Language; References; Methodological Perspectives for Surveying Rare and Clustered Population: Towards a Sequentially Adaptive Approach; 1 Introduction and Motivational Example.

2 Sampling Strategies2.1 Current Practice in TB Prevalence Surveys; 2.2 Adaptive Cluster Sampling as a Tool for Enhancing Case-Detection Ability; 2.3 List Sequential Sampling as a Tool for Dealing with Logistic Constraints; 3 Some Empirical Evidence; 4 Discussing Promising Perspectives: A First Step Towards an Integrated Strategy; References; 3 Age Management in Italian Companies. Findings from Two INAPP Surveys; Abstract; 1 Introduction; 2 Ageing Workforce in SMEs; 2.1 A Logistic Regression Model; 3 Age Management in Large Companies; 4 Conclusions; References.

4 Generating High Quality Administrative Data: New Technologies in a National Statistical Reuse PerspectiveAbstract; 1 Administrative and Statistical Data: A Problematic Convergence; 1.1 The European Vision; 1.2 The National Vision: Opportunities and Concerns; 1.3 Public Administrations; 1.4 IT Services; 2 Current Strategies Toward Network Administrative and Statistical System; 3 The Contribute of New Technologies; 4 Conclusions; References; 5 Exploring Solutions for Linking Big Data in Official Statistics; Abstract; 1 Introduction; 2 Standard Solutions in Official Statistics.

3 Issues in Linking Big Data4 A Case Study: Linking Internet-Scraped Data of Farmhouse to the Farm Register; 5 Concluding Remarks and Future Work Direction; References; Recent Debates in Statistics and Statistical Algorithms; An Algorithm for Finding Projections with Extreme Kurtosis; 1 Introduction; 2 Initialization; 3 Iteration; 4 Application; References; Maxima Units Search (MUS) Algorithm: Methodology and Applications; 1 Introduction; 2 The Methodology; 3 Simulation Study; 4 Applications; 4.1 Identification of Pivotal Units; 4.2 Tennis Singular Features; 5 Conclusions; References.

DESPOTA: An Algorithm to Detect the Partition in the Extended Hierarchy of a Dendrogram1 Hierarchical Agglomerative Clustering and the Issue of the Cut; 2 DEndrogram Slicing through a PermutatiOn Test Approach; 2.1 The Test Statistic as a Ratio of Two Costs; 2.2 The Permutation Distribution of the Test Statistic Under H0; 2.3 The Algorithm in Action; 3 Evaluating the Detected Partition; 4 Concluding Remarks and Future Avenues; References; The p-value Case, a Review of the Debate: Issues and Plausible Remedies; 1 Introduction; 2 Scientific Discoveries and Statistical Testing.