Correlation or Causation: The most common errors made in data analysis

The research field is prone to errors with significant consequences on generalizing results and interpreting statistical relationships.The following are some of the most common: Assuming you have a representative sample: This error is common especially in large data sets (big data). The results may look convincing, but the sample does not represent a true picture…

Codes & Reproducible Analysis

Data analysis should be reproducible! That is, a colleague should be able to look at your codes (yes codes) and clearly understand each step that was taken to produce your results. This is not as difficult as it sounds, since all the popular statistical software (e.g. SPSS, RATS, STATA and R-stats) all allow the analysts…

Jamaica and ‘Big Data’: The Future of Research

The emergence of 'big data' - the wealth of information being collected daily on customer behaviour and attitude via websites such as Facebook, Twitter, Linkedin etc - will cause a change in research as we know it. Internationally, the 'big data' discourse have gone a far way, however no mention has been made regarding its…