R, Python and MATLAB Data Analysis Service for Reproducible Research
Script-based analysis that you can rerun, audit and extend. We use R, Python and MATLAB to analyse data, build models and produce charts, and we hand over clean, commented code.
What we do in R
- Data cleaning and reshaping with the tidyverse
- Statistical tests, regression and mixed models
- Structural equation modelling and CFA with lavaan
- Complex survey analysis with the survey package
- Publication-quality graphics with ggplot2 and reports in R Markdown or Quarto
What we do in Python
- Data wrangling with pandas and numerical work with NumPy
- Statistical modelling with statsmodels and SciPy
- Machine learning with scikit-learn: classification, clustering and prediction
- Text processing and automation of repeated analyses and reports
- Charts with matplotlib and seaborn, and analysis notebooks in Jupyter
What we do in MATLAB
MATLAB is common in engineering and the physical sciences. We help with numerical analysis, simulation, signal and image data, curve fitting and statistical toolbox methods, and with converting existing MATLAB analysis into R or Python if you want an open-source workflow.
Why script-based analysis?
A script records every step from raw data to final figure, so results are reproducible, easy to check and quick to update when new data arrive. It also removes manual copy-and-paste errors. We comment the code, document the packages and versions used and, if you wish, explain how it works so your team can maintain it. If your supervisor or organisation prefers menu-driven software, see SPSS and STATA analysis. For specific methods, see regression analysis and structural equation modelling. If your project involves large amounts of text, our NLP and text analytics service uses the same tools.
How the work runs
- You share the data and describe the questions and desired outputs.
- We agree the approach and the tools to use.
- We write, test and document the code, and run the analysis.
- You receive the scripts, results, figures and a short guide to rerunning them.
Frequently asked questions
Should I use R or Python?
R is strongest for statistics, survey analysis and academic graphics. Python is strong for machine learning, automation and text work. We can advise on which suits your project, or use both.
Can you teach me to rerun the analysis?
Yes. We comment the code and can walk you through it so you can rerun and adapt it yourself.
Do you do machine learning?
Yes, including classification, clustering and prediction with proper validation, within reasonable project scope.
Can you automate a report that I produce every month?
Yes. A script or notebook can refresh the analysis, tables and charts each time new data arrive.
Do you work with MATLAB code I already have?
Yes. We can fix, extend or translate existing MATLAB code to R or Python.
Related statistical analysis services
SPSS & STATA Analysis
Analysis in SPSS and STATA with syntax and do-files you can rerun.
Regression Analysis
Linear, logistic, moderation and mediation models with diagnostics.
Descriptive & Inferential Statistics
Summaries, confidence intervals and tests that turn a dataset into conclusions.
Statistical Analysis Services
See every statistical method we support.
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