For a long time archaeologists had few options to deal with these problems because there were few alternative programs. The general alternative to using a point-and-click program is writing scripts to program algorithms for statistical analysis and visualisations. Writing scripts means that the data analysis workflow is documented and preserved, so it can be revisited in the future and distributed to others for them to inspect, reuse or extend. For many years this was only possible using ubiquitous but low-level computer languages such as C or Fortran (or exotic higher level languages such as S), which required a substantial investment of time and effort, and a robust knowledge of computer science. In recent years, however, there has been a convergence of developments that have dramatically increased the ease of using a high level programming language, specifically R, to write scripts to do statistical analysis and visualisations. As an open source programming language with special strengths in statistical analysis and visualisations, R has the potential to be a solution to the three problems of using software such as Excel and SPSS. Open source means that all of the code and algorithms that make the program operate are available for inspection and reuse, so that there is nothing hidden from the user about how the program operates (and the user is free to alter their copy of the program in any way they like, for example, to increase computation speed).
Blogs I Follow
- Great story on gender equality (er, lack thereof) in professional labor markets in Japan
- More annals of correlations wrongly attributed as causation: The more equal women and men are, the less they want the same things
- In happened sooner than I thought: Baobab beer in microbrewery in New Jersey
- Building housing in San Jose
- Readings on immigration issues in the United States
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