Excel Mathematics and Graphics: You covered many mathematical problem-solving techniques and many graphical presentation techniques throughout your college classes. Don’t underestimate the power of “simple” mathematics and graphics techniques just because you used them as freshmen and sophomores. You will differentiate yourself as an effective engineer when you summarize your work with simple graphical techniques, and you can explain your work with simple mathematical fundamentals.
Regression and Correlation — Shows how to use Excel regression and correlation tools to determine best linear y=mx+b fit to a set of (x,y) data.
Goal Seek Example — Gives four example for using the powerful Excel “Goal Seek” tool, used for iterative problems where you need to guess a solution value and then iterate until a solution is found. For narrative guidance link to the Goal Seek PowerPoint file.
Interpolation Demos — Examples and explanations for simple “single linear interpolation” and for more complicated “double interpolation”. Also see narrative guidance at the link How to Interpolate.
Basic Excel Functions and Examples — Download this file to explore various illustrative example problems in Excel. There are 16 example problems that highlight selected valuable functions in Excel. There is a lot you can accomplish in Excel, and this starter-kit will get you started as you create your own projects.
Bar Graphs Demos – Sampler of six example problems illustrating the power of Excel graphics to help others “see” trends and conclusions in your hard-earned data. If your application is “nearly like” one of the examples, the Save As… and delete the tabs you don’t need. No need to reinvent the wheel. No need to start from scratch when you have an example problem.
4th Order Runge Kutta Simulation: This Excel file demonstrates five examples, of increasing complexity, of solving an ordinary differential equation (dx/dt = f(x,t) ) using the classic 4th Order Runge-Kutta method. If you have a differential equation to solve, in other words you need to simulate a process that can be described analytically, then try RK4 simulation first and see what happens. You may save yourself a lot of hand wringing and research.
Basic Statistical Summary: This is a macro-enabled (xlsm) Excel file which performs a basic statistical analysis on any data set (can be a few dozen data points, or a few thousand). The summary report provides the expected statistics: average, standard deviation, median, minimum, maximum. A histogram of the data is compared to a comparable “normal distribution”. The VALUE of this tool is that it quantifies if your data set is “normally distributed” or “non-normal”. The selection of subsequent statistical analyses (like ANOVA) depend on normally distributed data.
Number Generator Tool: Use this macro-enabled (xlsm) Excel file to generate your choice of a normally-distributed data set for a mean and standard deviation; or a uniformly-distributed (random) data set between two limits; or a linear trend set of data; or a periodic trend set of data.
SPC Run Chart Demo: Download this Excel file for a full demo for setting up and maintaining a Statistical Process Control “Run Chart”. The trick is determining your process control variability limits. There are formal rules for determining these limits, and the demo shows how to do it. Also, check out and download the PPT file with narrative background on SPC.