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Market Research with Panels : Types, Surveys, Analysis, and Applications

International Migration and the Future of Populations and Labour in Europe

What a Coincidence! : On Unpredictability, Complexity and the Nature of Time

An introduction to statistical learning: with applications in R

Measure-Valued Branching Markov Processes

Octave and MATLAB for Engineering Applications

Market Research with Panels : Types, Surveys, Analysis, and Applications

Epidemiology: Principles and Practical Guidelines

CEMAF as a Census Method : A Proposal for a Re-Designed Census and An Independent U.S. Census Bureau

Statistical Analysis of Clinical Data on a Pocket Calculator, Part 2 : Statistics on a Pocket Calculator, Part 2

SPSS for Starters, Part 2

Agroforestry for Sustainable Land-Use Fundamental Research and Modelling with Emphasis on Temperate and Mediterranean Applications : Selected papers from a workshop held in Montpellier, France, 23–29 June 1997

Abductive Reasoning and Learning

From Experimental Network to Meta-analysis : Methods and Applications with R for Agronomic and Environmental Sciences

Computational Probability

Multivariate Reduced-Rank Regression : Theory, Methods and Applications

Recent Developments in Statistics and Data Science : SPE2021, Evora, Portugal, October 13-16

Advancements of Grey Systems Theory in Economics and Social Sciences

Random Perturbations of Dynamical Systems

Continuous-Time Markov Chains and Applications : A Singular Perturbation Approach

Understanding statistics and experimental design: how to not lie with statistics

An introduction to statistical learning: with applications in R - 103

A modern introduction to probability and statistics: understanding why and how

Linear mixed-effects models using R: a step-by-step approach

Applied Predictive Modeling

Applied Statistics for Business and Management using Microsoft Excel

Monte Carlo Methods in Financial Engineering - 53

Basic stochastic processes: a course through exercises

Applied probability and queues - 51

Generalized linear models with examples in R

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