This module explores the use of statistical software programs in analyzing quantitative data.

Learning Objectives

• Describe the benefits and uses of software programs in statistical analysis of quantitative data
• Compare and contrast the most used software packages

Quantitative studies often result in large numerical sets that would be cumbersome to analyze without the assistance of computer software packages. Programs such as EXCEL are relatively straight-forward and available to most researcher and are particularly useful descriptive statistics and less complicated analyses. Sometimes, the data analysis calls for a more sophisticated software package. Fortunately, there are several excellent statistical software packages available. Following is a list of three of the most popular programs. The Resource Links on this page provide additional options.

SPSS – The Statistical Package for Social Science (SPSS) is one of the most used software packages in social science research. One advantage is that is comprehensive and compatible with nearly any type of data file. SPSS is very user-friendly and can be used to run both descriptive statistics and other more complicated analyses. Data can be entered directly into the program will also generate reports, graphs, plots, and trend lines based on the data analyses.

STATA – This is an interactive program that can also be used for both simple and complex analyses. It will also generate charts, graphs and plots of your data and results. This program may seem a bit more complicated to some researchers. It uses four different windows including the command window, the review window, the result window, and the variable window. While it is a very useful program, the organization of this software may seem daunting.

SAS – The Statistical Analysis System (SAS) is another great statistical software package that can work with very large data sets. It has additional capabilities that make it commonly used in the business world because it can address issues such as business forecasting, quality improvement, planning, and so forth. It is a great program for data sets that need to incorporate strata, weighting, or groups. However, some knowledge of programming language is required to operate the software, making it a less appealing option for some.

The following SlideShare presentation, Introduction to SPSS, provides a basic introduction on how to use of a software package in data analysis. SPSS is one of the commonly used statistical software and the presentation describes how the software is used and includes examples.

SPSS lecture notes from David Mbwiga

Suggested Readings

Blaikie, N. (2003). Analyzing quantitative data: From description to explanation. Sage.

Bohrnstedt, G. W., & Knoke, D. (1994). Statistics for social data analysis.

Bryman, A., & Cramer, D. (1994). Quantitative data analysis for social scientists (rev. Taylor & Frances/Routledge.

Clark-Carter, D. (1997). Doing quantitative psychological research: From design to report. Psychology Press/Erlbaum (UK) Taylor & Francis.

Cramer, D. (2003). Advanced quantitative data analysis. McGraw-Hill International.

Creswell, J. W. (2002). Educational research: Planning, conducting, and evaluating quantitative. Prentice Hall.

Glass, G. V., & Hopkins, K. D. (1970). Statistical methods in education and psychology (p. 534). Englewood Cliffs, NJ: Prentice-Hall.

Suen, H. K., & Ary, D. (2014). Analyzing quantitative behavioral observation data. Psychology Press.