A Review of Software Tools for Quantitative Data Analysis

How to Get Started With Statistical Analysis

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If you're a sociology student or budding social scientist and have started to work with quantitative (statistical) data, analytic software will be very useful to you. These programs force researchers to organize and clean her data and offer pre-programmed commands that allow everything from very basic to quite advanced forms of statistical analysis. They even offer useful visualizations that will be useful as you seek to interpret your data, and that you may wish to use when presenting it to others.

There are many programs on the market, but unfortunately, they are quite expensive to purchase. The good news for students and faculty is that most universities have licenses for at least one program which students and professors can use. In addition, most programs offer a free, pared-down version of the full software package which will often suffice.

Here's a review of the three main programs that quantitative social scientists use.

Statistical Package for Social Science (SPSS)

SPSS is the most popular quantitative analysis software program used by social scientists. Made and sold by IBM, it is comprehensive, flexible, and can be used with almost any type of data file. However, it'sespecially useful for analyzing large-scale survey data. It can be used to generate tabulated reports, charts, and plots of distributions and trends, as well as generate descriptive statistics such as means, medians, modes and frequencies in addition to more complex statistical analyses like regression models.

SPSS provides a user interface that makes it easy and intuitive for all levels of users. With menus and dialogue boxes, you can perform analyses without having to write command syntax, like in other programs. It is also simple and easy to enter and edit data directly into the program. There are a few drawbacks, however, which might not make it the best program for some researchers.

For example, there is a limit on the number of cases you can analyze. It is also difficult to account for weights, strata and group effects with SPSS.

STATA

STATA is an interactive data analysis program that runs on a variety of platforms. It can be used for both simple and complex statistical analyses. STATA uses a point-and-click interface as well as command syntax, which makes it easy to use. STATA also make it simple to generate graphs and plots of data and results.

Analysis in STATA is centered around four windows: the command window, review window, result window and variable window. Analysis commands are entered into the command window and the review window records those commands. The variables window lists the variables that are available in the current data set along with the variable labels, and the results appear in the results window.

SAS

SAS, short for Statistical Analysis System, is also used by many businesses; in addition to statistical analysis, it also allows programmers to perform report writing, graphics, business planning, forecasting, quality improvement, project management and more. SAS is a great program for the intermediate and advanced user because it is very powerful; it can be used with extremely large data sets and can perform complex and advanced analyses.

SAS is good for analyses that require you to take into account weights, strata or groups. Unlike SPSS and STATA, SAS is run largely by programming syntax rather than point-and-click menus, so some knowledge of the programming language is required.

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Crossman, Ashley. "A Review of Software Tools for Quantitative Data Analysis." ThoughtCo, Mar. 2, 2017, thoughtco.com/quantitative-analysis-software-review-3026539. Crossman, Ashley. (2017, March 2). A Review of Software Tools for Quantitative Data Analysis. Retrieved from https://www.thoughtco.com/quantitative-analysis-software-review-3026539 Crossman, Ashley. "A Review of Software Tools for Quantitative Data Analysis." ThoughtCo. https://www.thoughtco.com/quantitative-analysis-software-review-3026539 (accessed December 18, 2017).