ezyStat is a UK-based statistical consultancy and research practice. It exists to give researchers, businesses and organisations direct access to rigorous statistical expertise, explained clearly.
To become a trusted provider of statistical expertise, quantitative research, data intelligence and evidence-based decision support for individuals, businesses, academic institutions and organisations worldwide.
To transform complex data into reliable evidence, meaningful insights and practical recommendations, through rigorous statistical methods, well-built analytical tools and accessible professional support.
Founder and Principal Statistician
Arash is a mathematical statistician with more than fifteen years in higher education and research. He has taught statistics, mathematics, research methods and programming at universities in the United Kingdom, New Zealand and Iran, and has supported learners and researchers at many different academic levels.
His teaching and research span statistical inference, probability, mathematical modelling and applied data analysis, with statistical programming in R and Python. That combination, of methodological depth and long practice in explaining it, is the basis of how ezyStat works.
Selected peer-reviewed papers co-authored by Dr Arash Ardalan, applying statistical methods to substantive research questions.
Cancer Informatics · 2024
Compares survival models to examine time to breast cancer recurrence and investigate associated patient and tumour characteristics.
BMC Pediatrics · 2022
Uses Bayesian network models to predict body composition from anthropometric measurements, with separate training and validation data.
Archives of Osteoporosis · 2021
Applies generalised additive models to examine how associations between body composition and bone density vary across the measurement range.
These commitments apply to every project, whatever its size or purpose.
Good analysis starts before the data. We plan studies so the evidence can answer the question asked, keep a written record of decisions, and report results with their uncertainty. Where artificial intelligence tools are used, they support the work under human review and never replace statistical judgement or handle confidential data without agreement.
We start with the decision or question behind the project, not the data.
We agree what will be measured, how, and what would count as a clear answer.
Sampling, instruments, models and power are specified before any data are collected.
Data are gathered or assembled, then checked for quality, completeness and bias.
Analysis follows the plan, with diagnostics and sensitivity checks on the key results.
You receive a clear report with recommendations, uncertainty and next steps.
Tell us about your project and discover how ezyStat can help you design, analyse and interpret your data.