Advantages of Statistical Analysis Software
Fortunately, in most applied statistics situations, calculations do not need to be done by hand. Computer software generally takes the “sting” out of the mathematical side of statistics and helps researchers focus on testing hypotheses and answering research questions.
For this discussion, conduct a Google search for other statistical analysis software packages besides Microsoft Excel’s Data Analysis ToolPak. Some examples include IBM’s SPSS Statistics, Minitab (developed by researchers at Penn State), and open-sourced RStudio, and there are others as well. Share a link to one software tool or a feature list of the software tool and develop an original response guided by these questions:
What are the advantages of Microsoft Excel over the software package you researched (aside from cost)?
What features does the software support that Microsoft Excel does not?
Which statistical tests does the software support that Microsoft Excel does not and under what conditions might they be needed?
Advantages of Statistical Analysis Software
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Advantages of Statistical Analysis Software
When it comes to data analysis, statisticians use computer software, such as International Business Machines Corporation’s (IBM) Statistical Package for Social Science (SPSS), to do the calculations. In particular, SPSS is used for batch processing, data storage, creating standard graphics, and data manipulation (IBM.com, n.d.). However, Microsoft Excel has various advantages over SPSS. First, it provides users with a broad range of charts and data visualization options, such as pie charts, bar graphs, and line charts. Second, Microsoft Excel has simple mathematical operations that are well-suited for handling small and medium-sized data. Third, it is a data formulation and computing software. Moreover, it is more flexible to organize and manipulate data in Microsoft Excel since statisticians can use worksheets.
On the contrary, SPSS can support specific features that Microsoft Excel cannot. SPSS is designed to handle statistical analysis for large datasets. For example, it can support regression analysis, t-tests, analysis of variance (ANOVA), data exploration, and factor analysis (Pallant, 2020). In addition, SPSS can handle large datasets effectively due to its data management capabilities, namely missing data handling, data mergin...