Statistics and data analysis
Descriptive statistics, hypothesis testing, regression, and the assumptions behind each method, taught step by step rather than as a checklist to memorize.
Mentorship
Learn the statistics and software your research actually needs.
One-to-one sessions for students and early researchers who want to understand the method, not just receive an output. We cover statistics, research analysis, software, programming, and introductory AI and machine learning, at a pace matched to where you are starting from.
What we cover
Pick the areas that match where you are.
Research methodology
Survey and questionnaire design, sampling logic, variable choices, and how to explain or defend a method decision in a viva or review.
Software and programming
Hands-on practice in R, Python, SPSS, Stata, or Excel, including variables, loops, functions, and scripts that a research workflow actually needs.
AI and machine learning basics
Core ideas behind common models and when an ML approach might fit a research question. Introductory exposure, not a substitute for thesis-level statistical analysis.
How sessions work
Sessions at your pace, not a fixed syllabus.
- 60–90 minute one-to-one sessions, online, at a frequency set in your learning plan.
- A short plan upfront: the topics, the order, and what each session should leave you able to do.
- Practice on your own coursework or data where that helps, alongside the core concepts.
- Session notes and resources you keep and can revisit after the program ends.
What this is not
Teaching, not a shortcut around the work.
No assignment completion
We teach the method and work through it with you. We do not complete graded assignments, exams, or vivas on your behalf.
No guaranteed grades
We can build real understanding and exam-ready practice. We do not promise marks, results, or approvals tied to academic evaluation.
No off-channel workflow
Session scheduling and materials stay on email and the contact form. We do not route mentoring through informal messaging apps.
Mentorship is for learning. It is not a workaround for graded work. Follow your department's rules on external tutoring and disclose support where required.
Start learning
Tell us what you want to learn and where you are starting from.
Share the subject, your current level, any deadline you are working toward, and the software you expect to use. We will come back with a short plan before any session is booked.