Excel - is easy to use for basic data analysis. Provides good charting and graphing. Excel can provide an easy way to enter your data even if you plan to use another tool for statistical analysis.
SPSS - has a graphical user interface. It is somewhat like Excel but provides buttons and widgets to do basic and advanced statistics. Procedures can be saved as scripts and used with additional datasets.
Stata - statistical analysis with enhanced data and matrix manipulation. In between SPSS and SAS in difficulty.
SAS - combines data management with statistical programming. It is good for complex datasets but may be challenging for beginners.
SAS JMP - JMP statistical discovery software from SAS is the tool of choice for scientists, engineers, and other data explorers in almost every industry and government sector. JMP combines powerful statistics with dynamic graphics in memory and on the desktop. Interactive and visual, JMP reveals insights that raw tables of numbers or static graphs tend to hide.
R - free statistical programming language. Very popular in many fields.
MATLAB - statistical programming language with good graphic output. Also used in engineering and other sciences.
Minitab - general purpose statistical software for easy interactive use and basic instruction
Tableau - a step up from Excel, Tableau is a powerful data visualization and analytics platform. While there are a number of license options, Tableau Public is free to use.
Voyant Tools - A web-based reading and analysis environment for digital texts. Also will create word or tag clouds and other text-based visuals.
Geographic Information Systems (GIS) are another big data visualization and analytics area. GIS uses spatial data to tell a story or solve a problem; more information on GIS at Miami University can be found in the guide below!