The MACMAS Lab supports research on JCSU’s campus across various disciplines. The computers in the lab support dual-boot (Mac, Windows, Linux and other Operating System platforms) technology. Highlights of the MACMAS Lab capabilities for conducting research include:
MatLab: A high-level language and interactive environment used by millions of engineers and scientists worldwide. It lets you explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, simulations and computational finance. There are many add-on toolboxes that extend MATLAB to specific areas of functionality, such as statistics, finance, image processing, bioinformatics, etc. Matlab is not a free software. However, there are clones like Octave, FreeMat, and Scilab which are free and have similar functionality.
MS Excel: One of the most popular tools of the MS Office suite that can be used for reporting and organizing data. Excel has statistical capability and can be used for basic analysis. Excel is often used to organize and build data sets that can be with the heavier statistical analysis tools. Excel is popular for reporting and graphing applications. It is very good general use tool that can support very big data sets (1 million rows)
Qualtrics: A web based software that allows the user to create surveys and generate reports without having any previous programming knowledge. The leading online survey software tool also conforms to IRBstandards for database management. Includes features that supports data analysis.
R is a programming language and software environment for statistical computing and graphics. The R language is an open source tool derived from the commercial S language and is widely used in academia. R is a command driven application as a result there are many GUls (graphic user interface) available that can sit on Rand enhance its user-friendliness. The most popular GUI is RStudio. Revolution R is a commercial version that supports big data projects.
RapidMiner Studio: a software platform developed by the company of the same name that provides an integrated environment for machine learning, data mining, text mining, predictive analytics and business analytics. It is used for business and industrial applications as well as for research, education, training, rapid prototyping, and application development and supports all steps of the data mining process including results visualization, validation and optimization. RapidMiner is developed on a business source model which means the core and earlier versions of the software are available under an OSI-certified open source license on Sourceforge.
SAS: This is one of the most popular analytic tools available across many disciplines and areas of study. It has great data management features as well as advanced analytic capabilities. Although it is very high priced, it is available free to academic institutions.
SPSS: One of the oldest and most popular general purpose statistical analysis tool for the social sciences. It is popular in the academic community for teaching basic and advanced statistics. IBM’s purchase of SPSS has increased the tool’s popularity and increased the tools capability with the addition of predictive analytic and business intelligence functions.
STATA: General purpose analytic tool that is popular in economics, sociology, political science, biomedicine, and epidemiology. STATA includes data management services, statistical analysis, graphics, simulations, and custom programming.
Tableau: Can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
Weka: (Waikato Environment for Knowledge Analysis) is a popular suite of machine learning software, developed at the University of Waikato, New Zealand. Weka, along with R, is amongst the most popular open source software used by the business community. The software is written in the Java language and contains a GUI for interacting with data files and producing visual results and graphs.