This weekend I read through "Statistics, Data Analysis and Decision Modeling" by James R. Evans and David L. Olson. The book caught my attention because of its emphasis on Excel. The authors review Excel plug-ins that are particularly helpful and easy to use.
I recently obtained more data on salinity in the Llobregat River, and would like to start analyzing the data in Excel before moving onto other software. While my most recent statistics course has made me more comfortable in R, I would like to max out Excel first. Everyone has Excel on their computers, and if I want to communicate my analysis, or facilitate collaborative learning with others, it makes sense to work on a platform that everyone is familiar with.
I took a special look at the chapters on forecasting and optimization. The plug-in "solver" can compute some simple linear and non-linear optimization problems. Going over the examples gave me some ideas about how to set up an optimization problem relevant to my dissertation, with simple constraints. Over time, my work may evolve into something more complex, but it makes sense to start with something straightforward. At the same time, there is no need to go over the top with mathematical complexity. As demonstrated by this book, programmers have developed impressive tools that are easy to use and communicate.
No comments:
Post a Comment