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Now showing items 11-20 of 46
5.1 - Introduction to Optimization & Analytical Sol.
(7/9/18)
In this lesson you'll learn about optimization, minimums, maximums, and a saddle. You’ll learn the difference between a local and global optima, the Second Derivative Test, contour lines, and how to graph a 2D function in Excel.
3.7 - Goal Seek and Solver
(7/6/18)
In this lesson you'll learn about how to use Excel's inbuilt root finding functions–goal seek for simple 1D function and Solver for multivariable functions.
2.1 - Taylor Series & Exp(x)
(6/15/18)
In this lesson you'll learn about what Taylor Series are and how to approximate the Exp(x) function using Taylor Series
7.1 - Trapezoidal Rule
(7/19/18)
In this lesson you'll learn about how to approximate an area under the curve using the Trapezoidal rule and how to develop a VBA code to implement this technique to any desired approximate error.
1.8 - Inbuilt Functions
(6/12/18)
In this lesson you'll learn about some the most useful and common EXCEL/VBA inbuilt functions used in numerical methods
7.3 - Romberg Integration
(7/26/18)
In this lesson you'll learn about how to approximate an area under the curve using Romberg Integration, how to develop a VBA code to implement this technique to any desired approximate error in addition to how Romberg ...
6.1 - Linear Regression
(7/13/18)
In this lesson you'll learn about how to best fit a line to a set of linear data points and how to develop a linear regression program. This is followed by a comparison of the results to Excel's inbuilt linear regression function
8.3 - Improvements on Euler (Heun's, Midpoint & Ralston)
(7/28/18)
In this lesson you'll learn about three techniques to improve Euler's Solution, and learn how to write a VBA program to apply all three techniques.
5.5 - Non Linear Optimization Using Solver
(7/14/18)
In this lesson you'll learn about how to use Excel's inbuilt Solver tool to solve optimization problems
4.7 - Debugging a Multiplication Code
(7/4/18)
In this lesson you'll learn about the common debugging issues that arise when programming numerical methods and how to best solve them and avoid them in the future.