About ezyStat
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.
Our vision
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.
Our mission
To transform complex data into reliable evidence, meaningful insights and practical recommendations, through rigorous statistical methods, well-built analytical tools and accessible professional support.
Dr Arash Ardalan
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.
Qualifications
- PhD in Mathematical Statistics
- MSc in Statistics
- BSc in Statistics
Research interests
- Bayesian methods
- Quantile regression
- Machine learning
- Applied data analysis
Experience
- Academic experience in the United Kingdom, New Zealand and Iran
- Teaching statistics, mathematics, research methodology, programming and quantitative subjects
- Statistical programming in R and Python
- Statistical inference, probability, mathematical modelling and applied data analysis
- Supporting learners and researchers at every academic level
Methodological principles
These commitments apply to every project, whatever its size or purpose.
- Statistical accuracy and methodological rigour
- Independence and objectivity
- Transparency and research integrity
- Confidentiality and data protection
- Practical, evidence-based recommendations
- Clear communication of complex results
- Accessibility and professional collaboration
- Responsible and ethical use of data and artificial intelligence
Our approach to research
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.
- 1
Understand the research question
We start with the decision or question behind the project, not the data.
- 2
Define the methodology
We agree what will be measured, how, and what would count as a clear answer.
- 3
Design the study
Sampling, instruments, models and power are specified before any data are collected.
- 4
Collect and validate data
Data are gathered or assembled, then checked for quality, completeness and bias.
- 5
Analyse and interpret
Analysis follows the plan, with diagnostics and sensitivity checks on the key results.
- 6
Deliver insights
You receive a clear report with recommendations, uncertainty and next steps.
Have a research question or data challenge?
Tell us about your project and discover how ezyStat can help you design, analyse and interpret your data.