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A pen and paper introduction to statistics

An introduction to spatial data science with GeoDaVolume 1,: Exploring spatial data

Time series : modeling, computation, and inference

Sparse graphical modeling for high dimensional data : a paradigm of conditional independence tests

Bayesian methods : a social and behavioral sciences approach

Handbook of approximate Bayesian computation

Spatial data science : with applications in R

Handbook of Bayesian variable selection

Data science for sensory and consumer scientists

Statistical methods for handling incomplete data

Foundations of data science with Python

Structural equation modeling using R/SAS : a step-by-step approach with real data analysis

Building your career as a statistician : a practical guide to longevity, happiness, and accomplishment

Bayesian nonparametrics for causal inference and missing data

Handbook of Bayesian, fiducial, and frequentist inference

Multidimensional stationary time series : dimension reduction and prediction

Semiparametric odds ratio model and its applications

Bayes rules! : an introduction to Bayesian modeling with R

Model-based clustering, classification, and density estimation using mclust in R

Foundations of data science with Python

Model-based clustering, classification, and density estimation using mclust in R

Handbook of multiple comparisons

Building your career as a statistician : a practical guide to longevity, happiness, and accomplishment

A pen and paper introduction to statistics

The theory of statistical implicative analysis : or the implausibility of falsehood ... when the exception confirms the rule

Graphics for statistics and data analysis with R

Graphics for statistics and data analysis with R

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