Every technology or a new invention has its own advantages and disadvantages. While advantages can be quickly understood and utilized, disadvantages cannot be found initially but can observed over a period of time. The same is with the software tools used for statistical analysis. Many of these tools are used by industry experts, academicians, researchers and students for research and analysis purposes. While many of the tools are accurate some tools might not produce accurate results. Also the decision of which tool to be used lies with the researchers and so every tool must be carefully selected. Some of the statistical tools require programming at basic levels or higher levels which every person might not be capable of. Other statistical tools which does not require coding has some limitations like model intervention which is limited. The main disadvantage of tools which use coding is that people require some time get trained and get expertise on the tool before using them.
Documentation can be a real problem for some of these software’s and the graphical user interfaces (GUIs) is also complicated in some software tools. Although many tools have multivariate graphical methods some of the features are limited in this area. Some tools cannot read or accept data from other packages or tools. The spreadsheet presentation may not be good and easy as that of excel and so people have to limit the beauties’ of the presentation to some extent. In some tools sophisticated and high level statistical tests are limited and some even might not have them. Some statistical tools require high level hardware tools or latest computers and might be slow on old computers. Use of any statistical tool requires basic knowledge of the tool and in-depth knowledge why such a particular process or analysis is required and being used. Without proper knowledge of statistics, these tools might not be helpful for layman.