54 PART 2 Examining Tools and Processes
We also provide guidance on how to choose between code-based and non–code-
based software, and end by providing advice on cloud data storage.
Considering the Evolution of
Statistical Software
The first widespread commercial statistical software invented is called SAS, and it
is still used today. SAS was developed originally in the 1960s and 1970s to run on
mainframe computers. Around 2000, SAS was adapted to personal computers
(known as PC SAS), adding a user-friendly graphical user interface (GUI). During
the growth of SAS, other commercial statistical packages appeared, the most pop-
ular being IBM’s SPSS. SAS continues to be the go-to program for big data analy-
sis, where analysts can easily access large datasets from servers. In contrast, SPSS
continues to be used on a personal computer like PC SAS.
If you were to take a college statistics course in the year 2000, your course would
have likely taught either SAS or SPSS. Professors would have made either SPSS or
SAS available to you for free or for a nominal license fee from your college book-
store. If you take a college statistics course today, you may be in the same
situation — or, you may find yourself learning so-called open-source statistical
software packages. The most common are R and Python. This software is free to
the user and downloadable online because it is built by the user community, not a
company.
As the Internet evolved, more options became available for statistical software. In
addition to the existing stand-alone applications described earlier, specialized
statistical apps were developed that only perform one or a small collection of spe-
cific statistical functions (such as G*Power and PS, which are for calculating sam-
ple sizes). Similarly, web-based online calculators were developed, which are
typically programmed to do one particular function (such as calculate a chi-square
statistic and p value from counts of data, as described in Chapter 12). Some web
pages feature a collection of such calculators.
Comparing Commercial to
Open-Source Software
Before 2010, if an organization performed statistical analysis as part of its core
function, it needed to purchase commercial statistical software like SAS or
SPSS. Advantages of implementing commercial software include the ability to