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  • Business Statistics, Global Edition + MyLab Statistics with Pearson eText - David Groebner
    Business Statistics, Global Edition + MyLab Statistics with Pearson eText
    David Groebner, Patrick Shannon and Phillip Fry
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  • Coding Ockham's Razor - Lloyd Allison
    Coding Ockham's Razor
    Lloyd Allison
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  • Applied Analytics through Case Studies Using SAS and R : Implementing Predictive Models and Machine Learning Techniques - Deepti Gupta
    Applied Analytics through Case Studies Using SAS and R
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    Deepti Gupta
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    Random Numbers and Computers
    Ronald T. Kneusel
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  • Graph Structures for Knowledge Representation and Reasoning : 5th International Workshop, GKR 2017, Melbourne, VIC, Australia, August 21, 2017, Revised Selected Papers - Gem Stapleton
    Graph Structures for Knowledge Representation and Reasoning
    5th International Workshop, GKR 2017, Melbourne...
    Gem Stapleton, Sebastian Rudolph, Pierre Marquis and Madalina Croitoru
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  • Domain-Specific Languages in R : Advanced Statistical Programming - Thomas Mailund
    Domain-Specific Languages in R
    Advanced Statistical Programming
    Thomas Mailund
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  • Elements of Copula Modeling with R : Use R! - Ivan Kojadinovic
    Elements of Copula Modeling with R
    Use R!
    Ivan Kojadinovic, Martin Machler, Marius Hofert and Jun Yan
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  • The Mata Book : A Book for Serious Programmers and Those Who Want to Be - William Gould
    The Mata Book
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    William Gould
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  • IPython Interactive Computing and Visualization Cookbook - Second Edition : Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook, 2nd Edition - Cyrille Rossant
    IPython Interactive Computing and Visualization Cookbook - Second Edition
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    Cyrille Rossant
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  • Language and Automata Theory and Applications : 12th International Conference, LATA 2018, Ramat Gan, Israel, April 9-11, 2018, Proceedings - Carlos Martin-Vide
    Language and Automata Theory and Applications
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    Carlos Martin-Vide, Shmuel Tomi Klein and Dana Shapira
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  • CABology : Value of Cloud, Analytics and Big Data Trio Wave - Nitin Upadhyay
    CABology
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    R Programming By Example
    Omar Trejo Navarro
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  • Using Excel for Business and Financial Modelling : A Practical Guide - Danielle Stein Fairhurst
    Using Excel for Business and Financial Modelling
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    Danielle Stein Fairhurst
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  • Bayesian Statistics in Action : BAYSM 2016, Florence, Italy, June 19-21 - Raffaele Argiento
    Bayesian Statistics in Action
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    Raffaele Argiento, Ettore Lanzarone and Isadora Antoniano Villalobos
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  • Intuitionistic Fuzzy Calculus : Studies in Fuzziness and Soft Computing - Qian Lei
    Intuitionistic Fuzzy Calculus
    Studies in Fuzziness and Soft Computing
    Qian Lei and Zeshui Xu
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  • The Basics of Item Response Theory Using R : Statistics for Social and Behavioral Sciences - Frank B. Baker
    The Basics of Item Response Theory Using R
    Statistics for Social and Behavioral Sciences
    Frank B. Baker and Seock-Ho Kim
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  • Statistical Disclosure Control for Microdata : Methods and Applications in R - Matthias Templ
    Statistical Disclosure Control for Microdata
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    Matthias Templ
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  • Educational Measurement for Applied Researchers : Theory into Practice - Hak Ping Tam
    Educational Measurement for Applied Researchers
    Theory into Practice
    Hak Ping Tam, Tsung-Hau Jen and Margaret Wu
    Hardcover
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  • Regression Modeling Strategies : With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis - Jr., Frank E. Harrell
    Regression Modeling Strategies
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  • Dynamic Documents with R and knitr : Chapman & Hall/CRC The R Series - Yihui Xie
    Dynamic Documents with R and knitr
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    Yihui Xie
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  • The R Student Companion - Brian Dennis
    The R Student Companion
    Brian Dennis
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  • A Student's Guide to the Study, Practice, and Tools of Modern Mathematics : Discrete Mathematics and Its Applications - Donald Bindner
    A Student's Guide to the Study, Practice, and Tools of Modern Mathematics
    Discrete Mathematics and Its Applications
    Donald Bindner and Martin Erickson
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  • Introduction to Statistics with SPSS for Social Science - Dennis Howitt
    Introduction to Statistics with SPSS for Social Science
    Dennis Howitt, Gareth Norris, Faiza Qureshi and Duncan Cramer
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  • Quantitative Investigations in the Biosciences using MINITAB - John Eddison
    Quantitative Investigations in the Biosciences using MINITAB
    John Eddison
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  • IBM SPSS Statistics 19 Made Simple - Colin D. Gray
    IBM SPSS Statistics 19 Made Simple
    Colin D. Gray and Paul R. Kinnear
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  • A Handbook of Statistical Analyses using R - Brian S. Everitt
    A Handbook of Statistical Analyses using R
    Brian S. Everitt and Torsten Hothorn
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  • Internet of Things, Smart Spaces, and Next Generation Networks and Systems : 17th International Conference, NEW2AN 2017, 10th Conference, ruSMART 2017, Third Workshop NsCC 2017, St. Petersburg, Russia, August 28-30, 2017, Proceedings - Olga Galinina
    Internet of Things, Smart Spaces, and Next Generation Networks and Systems
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    Olga Galinina, Yevgeni Koucheryavy, Sergey Balandin and Sergey Andreev
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  • Statistical Modelling of Survival Data with Random Effects : H-Likelihood Approach - Il Do Ha
    Statistical Modelling of Survival Data with Random Effects
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    Deep Learning in Natural Language Processing
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  • Analytical and Stochastic Modelling Techniques and Applications : 24th International Conference, ASMTA 2017, Newcastle-upon-Tyne, UK, July 10-11, 2017, Proceedings - Matthew Forshaw
    Analytical and Stochastic Modelling Techniques and Applications
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    Matthew Forshaw and Nigel Thomas
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  • Functional Statistics and Related Fields : Contributions to Statistics - Enea G. Bongiorno
    Functional Statistics and Related Fields
    Contributions to Statistics
    Enea G. Bongiorno, Ricardo Cao, Philippe Vieu and German Aneiros
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  • The Essentials of Data Science : Knowledge Discovery Using R - Graham J. Williams
    The Essentials of Data Science
    Knowledge Discovery Using R
    Graham J. Williams
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  • The Essentials of Data Science : Knowledge Discovery Using R - Graham J. Williams
    The Essentials of Data Science
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    Graham J. Williams
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  • Bayesian Analysis with Python : Unleash the power and flexibility of the Bayesian framework - Osvaldo Martin
    Bayesian Analysis with Python
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  • Growth Curve Models and Applications : Indian Statistical Institute, Giridih, India, March 28-29, 2016 - Ratan Dasgupta
    Growth Curve Models and Applications
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    Ratan Dasgupta
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  • Eigenvalue Problems: Algorithms, Software and Applications in Petascale Computing : EPASA 2015, Tsukuba, Japan, September 2015 - Shao-Liang Zhang
    Eigenvalue Problems: Algorithms, Software and Applications in Petascale Computing
    EPASA 2015, Tsukuba, Japan, September 2015
    Shao-Liang Zhang, Yusaku Yamamoto, Yoshinobu Kuramashi, Toshiyuki Imamura and Tetsuya Sakurai
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    Python for Finance - Second Edition
    Apply powerful finance models and quantitative ...
    Yuxing Yan
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    Corpus Linguistics and Statistics with R
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    Metaprogramming in R
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    Mastering Machine Learning with R - Second Edition
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    MATLAB® Essentials
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    Introduction to Geometric Algebra Computing
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    Intermediate Statistics Using SPSS
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  • Applied Statistical Methods in Agriculture, Health and Life Sciences - Bayo Lawal
    Applied Statistical Methods in Agriculture, Health and Life Sciences
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    Beginning Data Science with R
    Manas A. Pathak
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    Intuitive Probability and Random Processes using MATLAB®
    Steven Kay
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    A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R
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    Real Estate Analysis in the Information Age
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  • Probabilistic Cellular Automata : Theory, Applications and Future Perspectives - Francesca R. Nardi
    Probabilistic Cellular Automata
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  • Foundations of Fluid Mechanics with Applications : Problem Solving Using Mathematica® - Sergey P. Kiselev
    Foundations of Fluid Mechanics with Applications
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  • Statistics for Machine Learning : Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R - Pratap Dangeti
    Statistics for Machine Learning
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