Springer An Introduction to Statistical Data Science: Theory and Models

Mathematical Introduction to Data Science

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Introductory Statistics for Data Analysis

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Statistical Models and Methods for Data Science (Studies in Classification, Data Analysis, and Knowledge Organization)

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Math for Data Science

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Statistics for Data Science and Policy Analysis

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Mathematical Problems in Data Science: Theoretical and Practical Methods

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Data Science: Theory, Algorithms, and Applications (Transactions on Computer Systems and Networks)

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Statistical Modeling and Computation (Springer Texts in Statistics)

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Computing for Data Analysis: Theory and Practices (Data-Intensive Research)

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Computing for Data Analysis: Theory and Practices (Data-Intensive Research)

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Springer Innovations in Multivariate Statistical Modeling Book

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Advances and Innovations in Statistics and Data Science (ICSA Book Series in Statistics)

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Frame Theory in Data Science (Advances in Science, Technology & Innovation)

A Project-Based Introduction to Computational Statics

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Data Science and Statistics: Introduction to Data Science

Data Analysis of Medical Studies: Reading and Reporting

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Supervised and Unsupervised Statistical Data Analysis (Studies in Classification, Data Analysis, and Knowledge Organization)

Data Science and Internet of Things: Research and Applications at the Intersection of DS and IoT

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The Information Theory of Comparisons: With Applications to Statistics and the Social Sciences

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Data Science: Foundations and Hands-on Experience: Handling Economic, Spatial, and Multidimensional Data with R

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Springer Handbook of Engineering Statistics

Foundations of Applied Statistical Methods

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Regression Techniques for Data Analysis

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Springer - Theory Informing and Arising from Learning Analytics

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