0207 391 9038

Statistical Analysis & Representation

contact button

Services we can provide include but are not limited to:

statistical analysis

Correct statistical analysis is one of the most difficult aspects of primary research.

No matter whether you are using a specific data analysis program such as SPSS or Linux, or whether you take a purely descriptive and non-technical approach, the analysis of primary data can be an intimidating and distressing task.

If you plan to use a quantitative statistical analysis as part of your research project every aspect of your experimental design must be checked against the statistical test you plan to apply. Students, particularly Undergraduates, often come across serious problems when it comes to applying a valid and informative statistical test because their method did not meet the requirements of the test. There are various fundamental principles to experimental design including replication, randomisation and blocking techniques. Forgetting to include such principles in a methodology will result in an unnecessary, insignificant statistical result.

Statistics can be extremely simple or extremely complex. Often the problem lies with a poor understanding of statistics at the very basic level, leading to complete lack of understanding at higher levels.

One of the most common mistakes students make is in choosing the right statistical analysis to perform. For example one must decide whether the data is suitable for parametric or non-parametric testing.

Parametric testing

Important features of parametric testing include:

  • • ANOVAs
  • • Regressions
  • • Taking more than one explanatory variable into account
  • • Combining continuous and categorical variables
  • • Analysing interactions between explanatory variables
  • • Checking the statistical model is valid
  • • Model selection and experimental design.

Non-parametric tests

Non-parametric tests include:

  • • Chi-squared contingency tests
  • • Mann-Whitney test
  • • Kruskal-Wallis test
  • • Friedman's test

Oxbridge Primary Research employs nearly a thousand researchers, including many professors, PhD holders and professional scientists, working at the cutting edge of their fields, who are well-practised in analysing complex data. We can provide help with your statistics right from the planning stage of your experimental design through to the actual statistical analysis.

Statistical toolkits

Our researchers have a range of statistical toolkits at their disposal including, but not limited to:

  • • Minitab
  • • SPSS
  • • Stata
  • • Mathematica
  • • R
  • • Lab View
  • • GAUSS
  • • Octave
  • • O-matrix

Speak to us

If you are interested in our Statistical Analysis Service, one of our Primary Research Advisors would be happy to advise you on the right programs for your project and on all other aspects of the work.

To discuss The Statistical analysis service with one of our advisors, please call 0207 391 9038 or contact us via our contact form.