Statistics and Probabilities

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Statistical Analysis with Missing Data

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SAS for R Users: A Book for Data Scientists

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Probability, Random Variables, Statistics, and Random Processes: Fundamentals & Applications

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Modern Industrial Statistics: with applications in R, MINITAB and JMP

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Practical Applications Of Bayesian Relia

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Advanced Statistics with Applications in R

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Univariate, Bivariate, and Multivariate Statistics Using R: Quantitative Tools for Data Analysis and Data Science

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Introduction to Scilab: For Engineers and Scientists

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Statistical Process Control for the Food Industry: A Guide for Practitioners and Managers

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Multivariate Time Series Analysis and Applications

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Probably Not: Future Prediction Using Probability and Statistical Inference

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Statistics in Environmental Sciences

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Research Design and Analysis: A Primer for the Non-Statistician

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Statistical Physics for Electrical Engineering

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A Basic Course in Probability Theory

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Dynamics of Statistical Experiments

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Python for Probability, Statistics, and Machine Learning

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Statistical Rethinking: A Bayesian Course with Examples in R and STAN

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Data Visualization and Statistical Literacy for Open and Big Data

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Applied Multiple Imputation: Advantages, Pitfalls, New Developments and Applications in R

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Statistics for Beginners in Data Science: Theory and Applications of Essential Statistics Concepts using Python

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An Introduction to Categorical Data Analysis

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Introduction to Probability Models

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Introduction to Time Series Modeling with Applications in R

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Acceptance Sampling in Quality Control

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Bilinear Regression Analysis: An Introduction

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Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice

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Analyzing Dependent Data with Vine Copulas: A Practical Guide With R

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Functional Programming in R: Advanced Statistical Programming for Data Science, Analysis and Finance

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Supervised Machine Learning: Optimization Framework and Applications with SAS and R

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