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Statistical Analysis of Circular Data

. Statistical methods for handling such data have developed rapidly in the last twenty years, particularly data display, correlation, regression and;

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Data and Data Handling for AS Level Biology

. Data and Data Handling for AS Level Biology aims to address this weakness. The book provides examples, practice and examiners tips on how to;

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Principles of Statistical Data Handling

Data Handling shows readers how to input, manipulate, and debug their data to make substantive analysis easier and more accurate. Using a;

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Big Data Analytics (Database Management Systems)

. It elucidates the handling and storing of data through database management systems. It examines the challenges involved in big data analysis;

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Uncertainty Handling and Quality Assessment in Data Mining

fusion of many areas that are concerned with different aspects of data handling and data analysis, including databases, machine learning;

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Advances in Geo-Spatial Information Science

revised papers presented at the joint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science (Hong Kong;

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Statistical Analysis with Missing Data

methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple;

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Combinatorial Maps

in geometric modeling, computational and discrete geometry, computer graphics, and image processing and analysis, the book presents the data structures;

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Combinatorial Maps

in geometric modeling, computational and discrete geometry, computer graphics, and image processing and analysis, the book presents the data structures;

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Hands-On Data Science for Biologists Using Python

of data handling, preprocessing, and visualization. The book concludes with machine learning algorithms and their applications in biological data;

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Hands-On Data Science for Biologists Using Python

of data handling, preprocessing, and visualization. The book concludes with machine learning algorithms and their applications in biological data;

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Big Data in ehealthcare

This book focuses on the different aspects of handling big data in healthcare. It showcases the current state-of-the-art technology used;

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Spatial Data Handling in Big Data Era

discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data;

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Statistical Methods for Handling Incomplete Data

in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and;

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Metabolomics

concepts of metabolomics, including experimental design and technology Covers data handling, processing, analysis, data standards and;

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Spatial Data Handling in Big Data Era

discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data;

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Data Reduction and Error Analysis for the Physical Sciences

and graduate level, and to provide tools for data reduction and error analysis commonly required in the physical sciences. The presentation;

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Statistics For The Biosciences

Statistical techniques for the presentation and analysis of biological data are indispensable tools for the biologist. The purpose of this;

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Healthcare Data Analytics and Management

, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding;

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Analysis Of Longitudinal Data

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis;

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Statistical and Data Handling Skills in Biology

Statistical and Data Handling Skills in Biology puts statistics into context to show biology students the relevance of statistical analysis;

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Year 6

photocopiable sheets including graphs, charts, tables, tallies and other invaluable data handling tools and templates. Each lesson slideshow contains;

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Year 2

photocopiable sheets including graphs, charts, tables, tallies and other invaluable data handling tools and templates. Each lesson slideshow contains;

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Year 1

photocopiable sheets including graphs, charts, tables, tallies and other invaluable data handling tools and templates. Each lesson slideshow contains;

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Machine Learning Approaches for Urban Computing

details multiple types of data generating from urban activities and suitability of various machine learning algorithms for handling urban data;

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Big Data Application in Power Systems

distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning;

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Big Data Analytics Methods

solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data;

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