/BusinessAnalytics

Samples from Business Analytics: The art of modeling with spreadsheets implemented in R

Primary LanguageRMIT LicenseMIT

Business Analytics: The art of modeling with spreadsheet

This repo contains a R implementation of some of the samples found in Business Analytics: The art of modeling with spreadsheet. It does not contain the solutions to the exercises, so don't ask.

Motivation

This repo was started because while taking Anly 705 at Harrisburg University I realized that I needed to go the extra mile in my understanding. I could not just rely on Analytics Solver which is an Excel program that comes with the book. I needed to write down the formal declarations because some of the homework assigned needed to be more than just solutions. Moreover, some presented ambiguous requirements that could be interpreted different ways.

Organization

Folders correspond to the names of the chapters. Files correspond to the different sections. However, different editions of the book vary so YMMV. Also, I am only doing the samples for the chapters that are in the scope of the class that have a reasonable translation. As an example, chapter 5: Data Exploration and Preparation does not seem to have a direct equivalent. It is necessary to do in any data science project, but the principals carry, not necessarily the tasks. It could also be that the sample was assigned as a homework ot that I am behind on my personal goals.

Refrences

  1. Berkelaar, M et al. (2015). Interface to 'Lp_solve' v. 5.5 to Solve Linear/Integer Programs. [Online] https://CRAN.R-project.org/package=lpSolve
  2. Carnell, R. (2017). Provides the Standard Distribution Functions for the Triangle Distribution. [Online] https://cran.r-project.org/package=triangle
  3. Conceicao, E, Maechler, M. (2016). Differential Evolution Optimization in Pure R. [Online] https://CRAN.R-project.org/package=DEoptimR
  4. Konis, Kjell (2016). R Interface to 'lp_solve' Version 5.5.2.0. [Online] https://CRAN.R-project.org/package=lpSolveAPI
  5. Leschinski, C. H. (2018). Automatic Parallelized Monte Carlo Simulations. [Online] https://cran.r-project.org/package=MonteCarlo
  6. Powell, S. G., & Baker, K. R. (2016). Business Analytics: The art of modeling with spreadsheets. Wiley. [Online] http://faculty.tuck.dartmouth.edu/management-science/
  7. R Core Team. (2017). R: A Language and Environment for Statistical Computing. [Online] https://www.R-project.org/
  8. Ypma, Jelmer et al. (2017). nloptr: R interface to NLopt. [Online] https://CRAN.R-project.org/package=nloptr