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Statistical Learning and Data Sciences

This book constitutes the refereed proceedings of the Third International Symposium on Statistical Learning and Data Sciences, SLDS 2015;

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Classification, (Big) Data Analysis and Statistical Learning

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data;

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Applied Directional Statistics

of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted;

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Statistical Learning from a Regression Perspective

statistical learning; the impact of big data on statistical learning; the nature and consequences of post-model selection statistical inference;

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Quantitative Medical Data Analysis Using Mathematical Tools And Statistical Techniques

biomedical sciences. Topics include mathematical models for cancer invasion and clinical sciences, data mining techniques and subset selection;

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Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences

Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences A practical guide to the use of basic principles;

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The Practice of Statistics in the Life Sciences

statistical topics with examples and exercises drawn from across the life sciences, including the fields of nursing, public health, and allied health;

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A Handbook of Statistical Analyses Using SPSS

procedure applied to one or more data sets, primarily from the social and behavioral sciences areas. Each chapter also contains exercises relating;

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A Handbook of Statistical Analyses Using SPSS

procedure applied to one or more data sets, primarily from the social and behavioral sciences areas. Each chapter also contains exercises relating;

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Statistical Data Analysis Explained

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This;

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Introduction to Statistical Data Analysis for the Life Sciences

for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory;

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Machine Learning for Knowledge Discovery with R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction;

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Illustrating Statistical Procedures Finding Meaning in Quantitative Data

This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets;

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Illustrating Statistical Procedures Finding Meaning in Quantitative Data

This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets;

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Introduction to Statistical Machine Learning

Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and;

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Effective Statistical Learning Methods for Actuaries II

Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data;

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Applied Univariate, Bivariate, & Multivariate Stat istics

AN UPDATED GUIDE TO STATISTICAL MODELING TECHNIQUES USED IN THE SOCIAL AND NATURAL SCIENCES This revised and updated second edition;

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Introduction To Statistical Data Analysi

the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory;

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Advanced R Statistical Programming and Data Models

, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes;

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Computational Learning Approaches to Data Analytics in Biomedical Applications

using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms;

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Statistical Methods for Agricultural and Biological Sciences

STATISTICAL METHODS for Agricultural and Biological Sciences introduces basic statistical concepts as are required for understanding;

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Data Analysis Using SPSS

A concise introduction to data analysis for beginners and intermediate students using IBM - Statistical Package for Social Sciences (SPSS);

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Maximum Entropy and Bayesian Methods

Mexico, USA, from July 31 to August 4, 1995. Maximum entropy and Bayesian methods are widely applied to statistical data analysis and scientific;

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Statistics for the Behavioral Sciences

necessary data requirements, statistical procedures, and outcome interpretation. The workbook format of the text allow for students to complete;

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Using R for Data Analysis in Social Sciences

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for;

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Statistical Data Analytics

informatics and data analytics to practitioners who regularly apply statistical learning to their modern data.;

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Statistical Analysis of Longitudinal Categorical Data in the Social and Behavioral Sciences

of longitudinal categorical statistical methods. Each chapter provides basic methodology, helpful applications, examples using data from all fields of the;

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