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. This textbook, Exploratory Data Analysis in Business and Economics, aims to familiarise students of economics and business as well as;
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that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It;
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Discover and practice graphical exploratory analysis techniques across domains Book DescriptionHands-On Exploratory Data Analysis with R will;
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some of the preeminent statisticians of the 20th century, Understanding of Robust and Exploratory Data Analysis explains why and how to use;
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This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis. The reader will find numerous;
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developments and practical applications related to classification and clustering, data gathering, exploratory and multivariate data analysis;
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include randomization to eliminate bias, exploratory data analysis, graphs, expected value in bidding, the bootstrap, path analysis, robust;
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theory models, data envelopment analysis, and heuristic search procedures. The chapters on modeling examine exploratory and confirmatory factor;
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applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it;
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applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it;
Vergelijkbare producten zoals Applied Statistics and Multivariate Data Analysis for Business and Economics
theory models, data envelopment analysis, and heuristic search procedures. The chapters on modeling examine exploratory and confirmatory factor;
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theory and allowing them to make the most of data analysis techniques. Students learn through examples and applications of the most common;
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carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data;
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carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data;
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fundamental concepts of exploratory data analysis using Python Find missing values in your data and identify the correlation between different;
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An Applied Treatment of Modern Graphical Methods for Analyzing Categorical Data Discrete Data Analysis with R: Visualization and;
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...provides an important theoretical and philosophical extension to the currently popular statistical area of Exploratory Data Analysis, which seeks;
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Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four;
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Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four;
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Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that;
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readings selected in the process are subject to critical analysis and are complemented by an exploratory study of the financial services;
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readings selected in the process are subject to critical analysis and are complemented by an exploratory study of the financial services;
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"An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal;
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A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory;
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solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data;
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analysis points, multi-dimensional data analysis, and analysis of remote sensing data, cancer progression, chaos theory, epidemiological modeling;
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contexts is whether the structure of associations that underlies the data is accounted for by a latent construct. Exploratory factor analysis is a;
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