ISBN13: | 9781032507712 |
ISBN10: | 1032507713 |
Binding: | Paperback |
No. of pages: | 902 pages |
Size: | 254x178 mm |
Weight: | 1670 g |
Language: | English |
Illustrations: | 302 Illustrations, black & white; 5 Halftones, black & white; 297 Line drawings, black & white; 355 Tables, black & white |
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Probability and mathematical statistics
Applied mathematics
Mathematics in engineering and natural sciences
Engineering in general
Mechanical Engineering Sciences
Civil and construction engineering
Additional devices
Environmental sciences
Probability and mathematical statistics (charity campaign)
Applied mathematics (charity campaign)
Mathematics in engineering and natural sciences (charity campaign)
Engineering in general (charity campaign)
Mechanical Engineering Sciences (charity campaign)
Civil and construction engineering (charity campaign)
Additional devices (charity campaign)
Environmental sciences (charity campaign)
Engineering Data Analysis with MATLAB?
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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.
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.
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.