
Engineering Data Analysis with MATLAB?
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Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 30 December 2024
- ISBN 9781032506586
- Binding Hardback
- No. of pages902 pages
- Size 254x178 mm
- Weight 1830 g
- Language English
- Illustrations 302 Illustrations, black & white; 5 Halftones, black & white; 297 Line drawings, black & white; 355 Tables, black & white 675
Categories
Short description:
This uses MATLAB? for data analysis and statistics, offering a broad review of computational data analysis, in particular algebra, trigonometry, regression modeling, correlation, and graphical representation of results, covering both basic and more complex material, with a large number of worked examples and practice exercises.
MoreLong description:
This book provides a concise overview of a variety of techniques for analyzing statistical, scientific, and financial data, using MATLAB? to integrate several approaches to data analysis and statistics.
The chapters offer a broad review of computational data analysis, illustrated with many examples and applications. Topics range from the basics of data and statistical analysis to more advanced subjects such as probability distributions, descriptive and inferential statistics, parametric and non-parametric tests, correlation, and regression analysis. Each chapter combines theoretical concepts with practical MATLAB? applications and includes practice exercises, ensuring a comprehensive understanding of the material.
With coverage of both basic and more complex ideas in applied statistics, the book has broad appeal for undergraduate students up to practicing engineers.
MoreTable of Contents:
1. Getting Started. 2. Data Types and Visualization. 3. Random Variable and Probability Distribution. 4. Discrete Probability Distribution. 5. Continuous Probability Distribution. 6. Descriptive Statistics. 7. Inferential Statistics. 8. Parametric Tests. 9. Non-Parametric Testing. 10. Correlation. 11. Regression.
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