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Numerical Capplied computational pro...

Joyce, Philip.

Numerical Capplied computational programming with case studies /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Numerical Cby Philip Joyce.
其他題名:	applied computational programming with case studies /
作者:	Joyce, Philip.
出版者:	Berkeley, CA :Apress :2019.
面頁冊數:	xiv, 312 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	C (Computer program language)
電子資源:	https://doi.org/10.1007/978-1-4842-5064-8
ISBN:	9781484250648$q(electronic bk.)

Numerical Capplied computational programming with case studies /
Joyce, Philip.

Numerical Capplied computational programming with case studies /[electronic resource] :by Philip Joyce. - Berkeley, CA :Apress :2019. - xiv, 312 p. :ill., digital ;24 cm.

1. Introduction to C -- 2. Quadratic Formula -- 3. Integration by Trapezium Method -- 4. Monte Carlo Method of Integration -- 5. Matrices and Regression -- 6. Product Moment Correlation Coefficient -- 7. Further Monte Carlo Methods -- 8. Augmented Matrix Method For Simultaneous Equations -- 9. Economic / Financial Programming Case Study -- 10. Another Case Study -- Appendix A. Development Environment Reference -- Appendix B. Syntax Reference -- Appendix C. Answers to Exercises.

Learn applied numerical computing using the C programming language, starting with a quick primer on the C programming language and its SDK. This book then dives into progressively more complex applied math formula for computational methods using C with examples throughout and a larger, more complete application towards the end. Numerical C starts with the quadratic formula for finding solutions to algebraic equations that model things such as price vs. demand or rise vs. run or slip and more. Later in the book, you'll work on the augmented matrix method for simultaneous equations. You'll also cover Monte Carlo method model objects that could arise naturally as part of the modeling of a real-life system, such as a complex road network, the transport of neutrons, or the evolution of the stock market. Furthermore, the Monte Carlo method of integration examines the area under a curve including rendering or ray tracing and the shading in a region. Furthermore, you'll work with the product moment correlation coefficient: correlation is a technique for investigating the relationship between two quantitative, continuous variables, for example, age and blood pressure. By the end of the book, you'll have a feeling for what computer software could do to help you in your work and apply some of the methods learned directly to your work. You will: Gain software and C programming basics Write software to solve applied, computational mathematics problems Create programs to solve equations and calculus problems Use the trapezium method, Monte Carlo method, line of best fit, product moment correlation coefficient, Simpson's rule, and matrix solutions Write code to solve differential equations Apply one or more of the methods to an application case study.

ISBN: 9781484250648$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-5064-8doiSubjects--Topical Terms:

181957
C (Computer program language)

LC Class. No.: QA76.73.C15 / J693 2019

Dewey Class. No.: 005.133

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505 0 $a 1. Introduction to C -- 2. Quadratic Formula -- 3. Integration by Trapezium Method -- 4. Monte Carlo Method of Integration -- 5. Matrices and Regression -- 6. Product Moment Correlation Coefficient -- 7. Further Monte Carlo Methods -- 8. Augmented Matrix Method For Simultaneous Equations -- 9. Economic / Financial Programming Case Study -- 10. Another Case Study -- Appendix A. Development Environment Reference -- Appendix B. Syntax Reference -- Appendix C. Answers to Exercises.
520 $a Learn applied numerical computing using the C programming language, starting with a quick primer on the C programming language and its SDK. This book then dives into progressively more complex applied math formula for computational methods using C with examples throughout and a larger, more complete application towards the end. Numerical C starts with the quadratic formula for finding solutions to algebraic equations that model things such as price vs. demand or rise vs. run or slip and more. Later in the book, you'll work on the augmented matrix method for simultaneous equations. You'll also cover Monte Carlo method model objects that could arise naturally as part of the modeling of a real-life system, such as a complex road network, the transport of neutrons, or the evolution of the stock market. Furthermore, the Monte Carlo method of integration examines the area under a curve including rendering or ray tracing and the shading in a region. Furthermore, you'll work with the product moment correlation coefficient: correlation is a technique for investigating the relationship between two quantitative, continuous variables, for example, age and blood pressure. By the end of the book, you'll have a feeling for what computer software could do to help you in your work and apply some of the methods learned directly to your work. You will: Gain software and C programming basics Write software to solve applied, computational mathematics problems Create programs to solve equations and calculus problems Use the trapezium method, Monte Carlo method, line of best fit, product moment correlation coefficient, Simpson's rule, and matrix solutions Write code to solve differential equations Apply one or more of the methods to an application case study.
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