Six ways to work with data, one at a time or together

We take a raw dataset — survey responses, lab results, experiment logs, whatever you've collected — and run the statistics that answer your actual question: descriptive stats, hypothesis testing, correlation, regression, or ANOVA. You get a written report with the output explained in plain language, not just a table of numbers.

A survey is only as good as its design. We help write questions that avoid bias, work out a sampling plan that holds up to scrutiny, and set up the digital form (Google Forms, Kobo, ODK, or similar) so the responses come back structured and ready to analyse — not a column of free text you have to clean by hand.

If your team is re-building the same report in Excel every month, a dashboard usually pays for itself fast. We connect your sales, inventory, or operations data to Power BI or Tableau and build something your team can open and actually understand — filtered, labelled, and kept simple on purpose.

Support across the parts of a thesis that involve data: choosing a methodology that matches your research questions, running the analysis, writing the results chapter, and preparing you to defend your choices in a viva. We explain the reasoning behind each method so you can answer questions about it confidently.

A live, screen-shared call on Zoom, Google Meet, or Teams where we work through your dataset together — useful if you want to learn how to do the analysis yourself, or just want to talk through your results before a deadline. Sessions typically run 45 or 90 minutes, booked around your schedule.

Using AI tools alongside traditional statistical software to explore a dataset faster — spotting patterns, drafting summaries, and generating a first pass of visualisations in a fraction of the usual time. Every output is still checked by hand before it reaches you, so speed doesn't come at the cost of accuracy.