Scientific Data Analysis, Statistics & Biostatistics
Most laboratory data problems are not about running more tests — they are about knowing what the data you already have can support. Describe the data set and the decision it has to inform, and we route it to analysts with matching experience.
Typical work
- Statistical analysis plans written before data are collected
- Method comparison, equivalence and bias studies (e.g. Bland–Altman, Deming regression)
- Measurement uncertainty, gauge R&R and measurement system analysis
- Stability trending and shelf-life estimation
- Process capability, control charts and out-of-trend investigation
- Reliability and life-data analysis (Weibull, accelerated life models)
- Biostatistics for preclinical and clinical studies, including sample-size calculation
- Data cleaning, reproducible analysis code and visualisation
What you should receive
- The analysis plan, stated assumptions and the reason each method was chosen
- Results tables and figures with uncertainty, not just point estimates
- Reproducible code or a documented software workflow
- A plain-language interpretation, including the limits of what the data show
Before you brief an analyst
- The decision the analysis supports (release, comparison, claim, submission)
- Data format, size and how it was generated
- Any regulatory or customer expectation for the statistics used
- Confidentiality requirements for the raw data
How Laboratory Vortex fits in
Laboratory Vortex does not perform this work and is not a consultancy, testing laboratory or certification body. We take your request, check it is complete, and route it to providers whose published capabilities match. You compare scope, people and price, and contract with the provider directly.