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  • Financial Data Science with SAS - Babatunde O Odusami
    Financial Data Science with SAS
    Babatunde O Odusami
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  • Randomization Tests : Statistics: A Series of Textbooks and Monographs - Eugene Edgington
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    Eugene Edgington and Patrick Onghena
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  • PRACTICAL GUIDE TO LEARN ALGORITHMS : Master Algorithmic Problem-Solving Techniques (2024 Guide for Beginners) - MARTY TWITTY
    PRACTICAL GUIDE TO LEARN ALGORITHMS
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    MARTY TWITTY
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  • The Simple Guide to SAS : From Null to Novice - Kirby Thomas
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    Kirby Thomas
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  • Adaptive Filtering Under Minimum Mean p-Power Error Criterion - Wentao Ma
    Adaptive Filtering Under Minimum Mean p-Power Error Criterion
    Wentao Ma and Badong Chen
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  • Getting (more out of) Graphics : Practice and Principles of Data Visualisation - Antony Unwin
    Getting (more out of) Graphics
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    Antony Unwin
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  • Statistics Applied with the R Commander : Data Analysis Is (Not) an Art - Franz Kronthaler
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    Data Analysis Is (Not) an Art
    Franz Kronthaler
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  • Handbook of Statistical Analysis : AI and ML Applications - Robert Nisbet
    Handbook of Statistical Analysis
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    Robert Nisbet, Gary D. Miner and Keith McCormick
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  • Numerical Python : Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib - Robert Johansson
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    Robert Johansson
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  • Generalized Kernel Equating with Applications in R : Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences - Marie Wiberg
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    Marie Wiberg, Jorge Gonzalez and Alina A. von Davier
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  • Data Visualization : A Practical Introduction - Kieran Healy
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    Kieran Healy
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  • Analysis of Questionnaire Data with R - Bruno Falissard
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    Bruno Falissard
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  • Statistical Learning Tools for Electricity Load Forecasting : Mathematics and Statistics (R0) - Anestis Antoniadis
    Statistical Learning Tools for Electricity Load Forecasting
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    Anestis Antoniadis, Jairo Cugliari, Matteo Fasiolo, Yannig Goude and Jean-Michel Poggi
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  • Data Visualization with Microsoft Power BI : How to Design Savvy Dashboards - Alex Kolokolov
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    Alex Kolokolov and Maxim Zelensky
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  • Elementary Numerical Mathematics for Programmers and Engineers : Mathematics and Statistics (R0) - Gisbert Stoyan
    Elementary Numerical Mathematics for Programmers and Engineers
    Mathematics and Statistics (R0)
    Gisbert Stoyan and Agnes Baran
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  • Visualization and Imputation of Missing Values : With Applications in R - Matthias Templ
    Visualization and Imputation of Missing Values
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    Matthias Templ
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  • Predictive Analytics with KNIME : Analytics for Citizen Data Scientists - Frank Acito
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    Frank Acito
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  • A Hands-on Introduction to Big Data Analytics - Funmi Obembe
    A Hands-on Introduction to Big Data Analytics
    Funmi Obembe and Ofer Engel
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  • How to Use SPSS® : A Step-By-Step Guide to Analysis and Interpretation - Brian C. Cronk
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    Brian C. Cronk
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  • Machine Learning Methods : Computer Science (R0) - Hang Li
    Machine Learning Methods
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    Hang Li, Lu Lin and Huanqiang Zeng
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  • Joint Models for Longitudinal and Time-to-Event Data : With Applications in R - Dimitris Rizopoulos
    Joint Models for Longitudinal and Time-to-Event Data
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    Dimitris Rizopoulos
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  • Bayesian Data Analysis : Chapman & Hall/CRC Texts in Statistical Science - Andrew Gelman
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    Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson and Donald B. Rubin
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  • Matrix Algebra : Theory, Computations and Applications in Statistics - James E. Gentle
    Matrix Algebra
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    James E. Gentle
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  • The Digital Renaissance : Tracing the Evolution of Computers and Technology - Anu Joseph
    The Digital Renaissance
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    Anu Joseph
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  • Trajectory Optimization and Guidance Methods for Mars Entry : Engineering (R0) - Shuang Li
    Trajectory Optimization and Guidance Methods for Mars Entry
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    Shuang Li, Xu Liu, Xiu-qiang Jiang and Yu-ming Peng
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  • Bayesian Analysis with Python : A practical guide to probabilistic modeling - Osvaldo Martin
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    A practical guide to probabilistic modeling
    Osvaldo Martin
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  • Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers : 14th International Workshop, STACOM 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Revised Selected Papers - Oscar Camara
    Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers
    14th International Workshop, STACOM 2023, Held ...
    Oscar Camara, Esther Puyol-Antón, Maxime Sermesant, Avan Suinesiaputra and Alistair Young
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  • Diffusion Under Confinement : A Journey Through Counterintuition - Leonardo Dagdug
    Diffusion Under Confinement
    A Journey Through Counterintuition
    Leonardo Dagdug, Jason Peña and Ivan Pompa-García
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  • PROC FCMP User-Defined Functions : An Introduction to the SAS Function Compiler - Troy Martin Hughes
    PROC FCMP User-Defined Functions
    An Introduction to the SAS Function Compiler
    Troy Martin Hughes
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  • Statistical Tableau : How to Use Statistical Models and Decision Science in Tableau - Ethan Lang
    Statistical Tableau
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    Ethan Lang
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  • Hierarchical Archimedean Copulas : Mathematics and Statistics (R0) - Jan Górecki
    Hierarchical Archimedean Copulas
    Mathematics and Statistics (R0)
    Jan Górecki and Ostap Okhrin
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  • R语言计量金融初学指南 : Chinese Edition - Posts & Telecom Press
    R语言计量金融初学指南
    Chinese Edition
    Posts & Telecom Press
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  • Python Machine Learning By Example : Unlock machine learning best practices with real-world use cases - Yuxi (Hayden) Liu
    Python Machine Learning By Example
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    Yuxi (Hayden) Liu
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  • Cryptography Algorithms : Explore New Algorithms in Zero-knowledge, Homomorphic Encryption, and Quantum Cryptography - Massimo Bertaccini
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    Massimo Bertaccini
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  • Text and Math Into LaTeX - George Gratzer
    Text and Math Into LaTeX
    George Gratzer
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  • Audit Analytics : Data Science for the Accounting Profession - J. Christopher Westland
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    J. Christopher Westland
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  • Principles of Psychological Assessment : With Applied Examples in R - Isaac T. Petersen
    Principles of Psychological Assessment
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    Isaac T. Petersen
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  • Learn R : As a Language - Pedro J. Aphalo
    Learn R
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    Pedro J. Aphalo
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  • Data Science Fundamentals with R, Python, and Open Data - Marco Cremonini
    Data Science Fundamentals with R, Python, and Open Data
    Marco Cremonini
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  • Nonparametric Statistical Methods Using R : Chapman & Hall/CRC Texts in Statistical Science - John Kloke
    Nonparametric Statistical Methods Using R
    Chapman & Hall/CRC Texts in Statistical Science
    John Kloke and Joseph McKean
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  • Statistical Analysis with R Essentials For Dummies - Joseph Schmuller
    Statistical Analysis with R Essentials For Dummies
    Joseph Schmuller
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  • Introduction to Stochastic Processes Using R : Economics and Finance (R0) - Sivaprasad Madhira
    Introduction to Stochastic Processes Using R
    Economics and Finance (R0)
    Sivaprasad Madhira and Shailaja Deshmukh
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  • Applied Machine Learning Using mlr3 in R - Bernd Bischl
    Applied Machine Learning Using mlr3 in R
    Bernd Bischl, Raphael Sonabend, Lars Kotthoff and Michel Lang
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  • WAIC and WBIC with Python Stan : 100 Exercises for Building Logic - Joe Suzuki
    WAIC and WBIC with Python Stan
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    Joe Suzuki
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  • Statistics and Data Analysis for Engineers and Scientists : Intelligent Technologies and Robotics (R0) - Tanvir Mustafy
    Statistics and Data Analysis for Engineers and Scientists
    Intelligent Technologies and Robotics (R0)
    Tanvir Mustafy and Md. Tauhid Ur Rahman
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  • Artificial Intelligence and Multimedia Data Engineering : Volume 1 - Suman Kumar Swarnkar
    Artificial Intelligence and Multimedia Data Engineering
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    Suman Kumar Swarnkar, Sapna Singh Kshatri, Virendra Kumar Swarnkar and Tien Anh Tran
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  • R Programming for Actuarial Science - Peter McQuire
    R Programming for Actuarial Science
    Peter McQuire and Alfred Kume
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  • Excel 2024 : Mastering Charts, Functions, Formula and Pivot Table in Excel 2024 as a Beginner with Step by Step GuideMastering Charts, Functions, Formula and Pivot Table in Excel 2024 as a Beginner with Step by Step Guide - Thomas Reynolds
    Excel 2024
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  • IBM SPSS Statistics 29 Step by Step : A Simple Guide and Reference - Darren George
    IBM SPSS Statistics 29 Step by Step
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  • Theory and Applications of Time Series Analysis : Selected Contributions from ITISE 2022 - Olga Valenzuela
    Theory and Applications of Time Series Analysis
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  • Incentive Mechanism for Mobile Crowdsensing : A Game-theoretic Approach - Youqi Li
    Incentive Mechanism for Mobile Crowdsensing
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    Youqi Li, Fan Li, Song Yang and Chuan Zhang
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  • Sustainable Statistical and Data Science Methods and Practices : Reports from LISA 2020 Global Network, Ghana, 2022 - O. Olawale Awe
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    O. Olawale Awe and Eric A. Vance
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  • R Programming : Statistical Data Analysis in Research - Kingsley Okoye
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  • Developments in Statistical Modelling : Springer Nature Proceedings excluding Computer Science - Jochen Einbeck
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  • Bayesian Programming : Chapman & Hall/CRC Machine Learning & Pattern Recognition - Pierre Bessiere
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  • Causality for Artificial Intelligence : From a Philosophical Perspective - Jordi Vallverdú
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  • Smart Medical Imaging for Diagnosis and Treatment Planning - Nilanjan Dey
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    Nilanjan Dey, Bitan Misra and Sayan Chakraborty
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  • Introduction to Data Science : Data Wrangling and Visualization with R - Rafael A. Irizarry
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  • Applied Medical Statistics Using SAS - Geoff Der
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  • Matrix Structural Analysis and the Finite Element Methods Using Scilab and Octave : A Problem-Solving Approach - Bedilu Habte
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  • Producing High-Quality Figures Using SAS/GRAPH and ODS Graphics Procedures - Charlie Chunhua Liu
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  • An R Companion to Linear Statistical Models - Christopher Hay-Jahans
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  • Probability Theory : An Introduction Using R - Shailaja R. Deshmukh
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  • Modern Statistics with R : From Wrangling and Exploring Data to Inference and Predictive Modelling - Måns Thulin
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  • Data Science : A First Introduction with Python - Tiffany Timbers
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  • Introduction to Numerical and Analytical Methods with MATLAB® for Engineers and Scientists - William Bober
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  • Computational Statistics : An Introduction to R - Günther Sawitzki
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  • Mimetic Discretization Methods - Jose E. Castillo
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  • Machine Learning, Animated : Chapman & Hall/CRC Machine Learning & Pattern Recognition - Mark Liu
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  • The Model Thinker : What You Need to Know to Make Data Work for You - Scott E. Page
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  • Complex Network Analysis in Python : Recognize - Construct - Visualize - Analyze - Interpret - Dmitry Zinoviev
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