Statistical analysis

regression analysis

The essentials

Statistical analysis brings meaning to data; drawing out insights, solutions and evidence. 

Analysis can take many forms, from simple summary statistics to processing large and complex data sets and statistical modelling (particularly in a medical statistics) to time series, simulation studies, longitudinal data analysis, survival models and randomisation tests.

A proper and robust analysis is it offers a measure of certainty and validity which allows confidence in decision making.


The application of a proper statistical analysis to data can yield results which are far  richer and robust than what a basic interrogation would offer. This adds value to analysis and thus offers insights beyond what would otherwise be achieved, insights which can lead to significant breakthroughs or leaps in understanding.

Our consulting services have helped many individuals, organisations and companies across a broad range of sectors including, but not limited to, medical devices, pharmaceuticals, agriculture and academia.

Types of statistical analysis include summary statistics and formal statistical analysis


  • Summary statistics: An important aspect of descriptive statistics, summary statistics are used to summarise and communicate the largest amount of data in the quickest way possible giving important headlines, presenting your results in a simple and effective way.
  • Formal statistical analysis: Ranging from hypothesis testing to predictive modelling, formal statistical analysis is the purest form of statistics. Used when specific questions need to be answered, these analyses consider multiple variables and require detailed understanding of the question and the environment in which it applies.