Numerical methods and analysis is the study of mathematical techniques for solving problems that arise in the natural and social sciences. It is a powerful tool for solving problems that are too difficult or impossible to solve analytically. In addition, numerical methods can be used to understand the behavior of complex systems and to compare different models.
This article is all about helping you get to know the Numerical Methods & Analysis for PC better and install it on your PC. Here are the technical specifications you want to know about beforehand:
How To Install & Download Numerical Methods & Analysis For PC Windows 10/8/7
To install the Numerical Methods & Analysis on your computer, you need to install the NOX payer first. To do that, as well as install the Numerical Methods & Analysis, follow the easy guide below from start to finish:
- First, start by downloading the NOX player. It should store in your download folder in your computer.
- Locate the installer, double click on it, and let it install on your PC. It will take a few minutes to complete the installation.
- Once installed, you’ll have the option to start the emulator. Go ahead and start the emulator. It will set up the environment for the first time.
- Now, open the Play store app (It’s on the top header, or you can search for it) and it will ask you to log in. Log into your Google account.
- Search for the Numerical Methods & Analysis app on the Play store app and the app will show up in the first position. Click and start installing the app on your computer.
Numerical Methods & Analysis Andorid App Summary
Under the Education category on Google Play store, Numerical Methods & Analysis has over 47750 of downloads reflecting the number of users they have. Engineering Apps has developed the Numerical Methods & Analysis and has improved a lot to this day with the latest version, 6.0.
Until this latest version, Numerical Methods & Analysis has successfully been able to acquire a good user rating of 3.6. This latest version was last updated on Mar 10, 2020 which you can check in the technical specification section below.
The only bummer here is you can not just download and install it on your computer without using an Android emulator. However, you can definitely install it on your computer by using one of the most popular emulators: NOX player, BlueStacks, or Memu Emulator.
These tools will help you install and use the Numerical Methods & Analysis on your computer without having to use your Phone. To do so, you need to follow the guides we’re about to discuss in this article.
|App Name:||Numerical Methods & Analysis On Your PC|
|Devoloper Name:||Engineering Apps|
|Supporting OS:||Windows,7,8,10 & Mac (32 Bit, 64 Bit)|
|Updated on:||Mar 10, 2020|
|Get it On:|
Features of Numerical Methods & Analysis for PC
13. Gauss-Jordan Method
14. Gauss-Kronrod Method
15. Jacobi Method
16. Gauss-Newton Method
17. Secant Method
18. Bisection Method
19. Fixed Point Iteration
20. Newton Method
21. Regula-Falsi Method
22. Muller’s Method
23. Orthogonal Trapezoidal Rule
24. Simpson’s Rule
25. Romberg Integration
26. Trapezoidal Rule
27. Rectangular Rule
28. Midpoint Rule
29. Euler’s Method
30. Modified Euler’s Method
31. Runge-Kutta Method of Second Order
32. Milne’s Method
33. Adams’ Method
34. Heun’s Method
35. Trapezoidal-Heun Method
36. predictor-corrector Method
37. Method of Steepest Descent
38. Newton Method with Conjugate Gradients
39. Krylov Subspace Method
40. Limited Memory BFGS Method
41. Conjugate Gradient Method
42. Quasi-Newton Method
43. Broyden’s Method
Numerical Methods & Analysis App Overview and Details
The app is a complete free handbook of Numerical Methods & Analysis which covers important topics, notes, materials & news on the course. Download the App as a reference material & digital book for Mathematics & mechanical engineering programs & degree courses. The study is also used extensively in Artificial intelligence, algorithms, real time systems and machine learning.
This useful App lists 77 topics with detailed notes, diagrams, equations, formulas & course material, the topics are listed in 5 chapters. The app is must have for all the engineering science students & professionals.
The app provides quick revision and reference to the important topics like a detailed flash card notes, it makes it easy & useful for the student or a professional to cover the course syllabus quickly just before an exams or job interviews.
Also get the hottest international engineering & technology news on your app powered by Google news feeds. We have customised it so that you get regular updates on subject from international/national colleges, universities, research, industry, applications, engineering, tech, articles & innovation.
This is the best application to remain updated on your fav. subject.
Use this useful engineering app as your education tool, utility, tutorial, book, a reference guide for syllabus and explore study course material, aptitude tests & project work.
Track your learning, set reminders, edit, add favourite topics, share the topics on social media.
Some of the topics Covered in this application are:
1. Solution of algebraic and transcendental equations
2. Methods of solving roots of polynomial equations
3. Initial Approximation for an Iterative Procedure
4. Method of False Position
5. Newton-Raphson Method
6. General Iteration Method
7. Convergence of the Iteration Methods
8. Linear system of algebraic equations
9. Direct method for solving linear system
10. Guass elimination method
11. Guass jordan method
12. Iterative Methods
13. Gauss-Jacobi Iteration Method
14. Gauss-Seidel Iteration Method
15. Eigen value problems
16. Power method
18. Lagrange Interpolation
19. Linear Interpolation
20. Quadratic interpolation
21. Error of interpolation
22. Divided differences
23. Newton’s Divided Difference Interpolation
24. Interpolation With Evenly Spaced Points
25. Relations between differences and derivatives
26. Newton’s forward difference formula
27. Newton’s Backward Difference Interpolation Formula
28. Spline function
29. Cubic Interpolation
30. Numerical Differentiation
31. Derivatives Using Newton’s Forward Difference Formula
32. Derivatives Using Newton’s Backward difference Formula
33. Derivatives using Divided Difference Formula
34. Numerical Integration and Integration Rules Based on Uniform Mesh Spacing
35. Trapezium Rule
36. Error in Trapezium Rule
37. Composite trapezium rule
38. Simpson’s 1/3 Rule
39. Error in Simpson’s 1/3 Rule
40. Composite Simpson’s 1/3 Rule
41. Simpsom’s 3/8 Rule
42. Romberg Method
43. Romberg method for the trapezium rule
44. Romberg method for the Simpson’s 1/3 Rule
45. Gauss-Legendre Integration Rules
46. Gauss one point rule (Gauss-Legendre one point rule)
47. Gauss Two point rule (Gauss-Legendre Two point rule)
48. Gauss Three point rule (Gauss-Legendre Three point rule)
49. Evaluation of Double Intergral Using Trapezium Rule
50. Evaluation of Double Intergral Using Simpson’s rule
51. Introduction to Initial Value Problem for Ordinary Differential Equations
52. Reduction of second order equation to a first order system
53. Single Step Method
54. Multi step Methods
55. Taylor series Method
56. Modified Euler or Heun’s Methods
57. Runge Kutta Methods
Each topic is complete with diagrams, equations and other forms of graphical representations for better learning and quick understanding.
Numerical Methods & Analysis is part of Mathematics & mechanical engineering education courses and technology degree programs of various universities.
Whats New In this Numerical Methods & Analysis?
Check out New Learning Videos! We have Added
• Chapter and topics made offline access
• New Intuitive Knowledge Test & Score Section
• Search Option with autoprediction to get straight the your topic
• Fast Response Time of Application
• Provide Storage Access for Offline Mode
In conclusion, numerical methods and analysis are powerful tools that can be used to solve a variety of mathematical problems. They can be used to accurately approximate the results of complex mathematical problems, and can be used to help researchers understand the behavior of complex systems. Additionally, they can be used to improve the efficiency of mathematical algorithms.
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