Software and Programs

This free and open source program is among one of the most popular data science platforms that combines a number of Python and R programs in a single interface. Includes Juypter Notebook, JupterLabs, Spyder, Qt Console, and RStudio among others. Is as difficult or easy to use as the program being used within Anaconda. Be aware you need to use the Anaconda Prompt  to update Anaconda and the programs within Anaconda so you will need to have some comfort with using console user interface and command line interface is necessary. 

One of the most commonly used programs in the social sciences and business- is easy to learn how to use due to the availability of free trainings-but can be difficult to access due to its expense and multiple package options. Considered more of a program for beginners since it does not do all higher level analyses.

This is a free program that is similar to SPSS in many ways. It performs descriptive statistics, most bivariate analyses, linear regression, logistic regression, measures of association, cluster analysis, reliability and factor analysis, and non-parametric tests.

Free and open source code text editor that allows for easy collaboration on coding and data projects. Works well with Python and can have packages installed that allow it to work seamlessly with Git and GitHub. Like most Python integrated development environments (IDE), you will need to download a series of packages to fully use Atom for data analysis. 

Although Git is generally used as a development framework for those creating software, GitHub can be used by to share computer code, data analysis techniques, and collaborate on data projects. GitHub is a repository, or "repo", that allows for a wide amount of sharing for open source code so you can download and edit code created by other researchers and tailor it to your needs. Remember, give credit to other data scientists who provide you with helpful material and do your best to pay it forward and share your own projects, when possible!