Exploratory Data Analysis with MATLAB
Author Description
Exploratory data analysis (EDA) was conceived at a time when computers were not widely used, and thus computational ability was rather limited. As computational sophistication has increased, EDA has become an even more powerful process for visualizing and summarizing data before making model assumptions to generate hypotheses, encompassing larger a
Menrva's Summary
THE THESIS
This text investigates the application of exploratory data analysis (EDA) techniques within the MATLAB computational environment to facilitate robust data visualization and hypothesis generation. The authors, experts in statistical computing and data analysis, provide a comprehensive framework for utilizing MATLAB's advanced computational capabilities to handle modern, large-scale datasets. By bridging traditional EDA concepts with contemporary software tools, the book establishes a methodology for summarizing complex data structures before formal statistical modeling begins.
THE SCOPE MAP
What You Will Find
- Computational techniques for visualizing high-dimensional data sets
- MATLAB-specific functions and toolboxes for statistical analysis
- Methodologies for identifying data patterns and outliers
- Practical case studies demonstrating data summarization workflows
THE AUTHORITY PERSPECTIVE
Experts recognize this work as a technical resource for practitioners who require a structured approach to data exploration using MATLAB. Readers frequently note the academic density of the prose and the focus on practical implementation over theoretical abstraction.
Page Count:
0
Publication Date:
2004-01-01
Publisher:
Taylor & Francis Group
ISBN-10:
0203483375
ISBN-13:
9780203483374
Multivariate analysis
Mathematics
Programming
Technology
Statistics
Data Science
MATLAB Computer Program
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