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topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental;
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This book provides an introduction to R programming and a summary of financial mathematics. It is not always easy for graduate;
Vergelijkbare producten zoals R Programming and Its Applications in Financial Mathematics
This book provides an introduction to R programming and a summary of financial mathematics. It is not always easy for graduate students;
Vergelijkbare producten zoals R Programming and Its Applications in Financial Mathematics
Hands-on analysis of actual financial data Accessible coverage of statistical methods Exercises to reinforce concepts;
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illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and;
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to practitioners with financial data analysis concerns.;
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characterize modern financial markets. The first two sections appeal to readers with technical backgrounds, describing data analysis and ways;
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statistical modeling and analysis of MRI data. Offering a practical introduction to the field, the book focuses on those problems in data analysis for;
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with Mayes' FINANCIAL ANALYSIS WITH MICROSOFT (R) EXCEL (R), 9E. This edition provides a reader-friendly solid foundation in corporate finance;
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starting point to access the rich information that comes bundled with R. Accessible to a broad audience, this book explores key topics in data;
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how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks;
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FINANCIAL ANALYSIS WITH MICROSOFT (R) EXCEL (R) 2016, 8E, equips you with a solid foundation in corporate finance while helping you maximize the;
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;
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featuring PowerPoint(R) slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second;
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encountered while performing data analysis. Style and approach This easy-to-follow guide is full of hands-on examples of data analysis with R;
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With an emphasis on social science applications, Event History Analysis with R, Second Edition, presents an introduction to survival and;
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students. It uniquely combines a hands-on approach to data analysis - supported by numerous real data examples and reusable [R] code - with a;
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series with continuous models, how to calibrate them from discrete data and further covers option pricing with one or more underlying assets;
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This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics;
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for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises;
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, hypothesis testing, linear regression analysis, and clustering with two appendices on installing and using R and R-Commander. A novel feature of this;
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apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as;
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Qualitative and Mixed Methods Data Analysis Using Dedoose (R): A Practical Approach for Research Across the Social Sciences provides both;
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This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry;
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researchers lack the statistical skills or resources that would allow them to explore their data to its full potential. Introduction to Data Analysis;
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introduction to the interconnection between these research fields. It thus provides the reader with the intellectual groundwork indispensable for;
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