The top four things that I want to share about the use of statistics and statistical tools are:
- Most statistical tests/approaches are not widely used. Only Correlation, Regression, z- or t-tests, and Cluster Analysis have been used by more than 50% of the participants in this research, during the first half of 2017 – and this sample probably over-represents people using statistics, and under-represents those using statistics less often.
- SPSS is the dominant software package amongst people using statistical packages. Given SPSS is approaching 50 years old, that may not be the sign of a dynamic industry? But, there are many people using tools such as Q, Sawtooth Software, SAS – and beyond them programs such as Latent Gold, Tableau, and XLSTAT.
- One of the growth areas is the use of tools is the use of integrated data collection / analysis solutions, for example Confirmit, Askia, Vision Critical, Qualtrics. The use of these tools requires the researcher to make fewer decisions. For example, survey monitoring flows into the analysis without any extra steps, the packages have a default way of looking of testing differences (for example t-tests) – making it less likely that the researcher will consider less convenient options, such as Chi-squared tests.
- The most widely adopted complex solution is R, an open-source programming language that leverages large numbers of libraries for things like advanced analytics, data science, and data visualisation. People have been highlighting the growing role of R for a few years, and it seems to be gaining a stronger share of market research and insight analyses.