Statistics and Probabilities

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Avoiding Data Pitfalls: How to Steer Clear of Common Blunders When Working with Data and Presenting Analysis and Visualizations

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Basic and Advanced Statistical Tests: Writing Results Sections and Creating Tables and Figures

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Basic Statistics and Epidemiology

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Bayesian and High-Dimensional Global Optimization

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Bayesian Applications in Environmental and Ecological Studies with R and Stan

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Bayesian Modelling of Spatio-Temporal Data with R

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Bayesian Statistics for the Social Sciences 2nd Edition

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Bayesian Thinking in Biostatistics

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Becoming a Data Head: How to Think, Speak and Understand Data Science, Statistics and Machine Learning

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Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist

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Bilinear Regression Analysis: An Introduction

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Bio-mathematics, Statistics, and Nano-Technologies: Mosquito Control Strategies

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Biomarker Analysis in Clinical Trials with R

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Business Statistics for Competitive Advantage with Excel 2019 and JMP: Basics, Model Building, Simulation and Cases

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Business Statistics For Dummies 2nd Edition

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Case Studies in Bayesian Statistical Modelling and Analysis

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Categorical and Nonparametric Data Analysis: Choosing the Best Statistical Technique (Multivariate Applications Series) 2nd Edition

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Chemical Thermodynamics and Statistical Aspects: Questions to Ask in Fundamentals and Principles

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Chi-squared Goodness-of-fit Tests for Censored Data

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Classical Clifford Algebras: Operator-Algebraic and Free-Probabilistic Approaches

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Computational and Statistical Methods for Chemical Engineering

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Computational Aspects of Psychometric Methods: With R

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Computational Bayesian Statistics: An Introduction

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Contributions on Theory of Mathematical Statistics

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Credit Intelligence & Modelling: Many Paths through the Forest of Credit Rating and Scoring

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Data Analysis and Applications 1: Clustering and Regression, Modeling-estimating, Forecasting and Data Mining, Volume 2

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Data Analysis and Applications 2: Utilization of Results in Europe and Other Topics, Volume 3

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Data Analysis and Applications 3: Computational, Classification, Financial, Statistical and Stochastic Methods

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Data Analysis and Applications 4: Financial Data Analysis and Methods

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Data Analysis: What Can Be Learned From the Past 50 Years

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