R & RStudio Analysis
Reproducible analysis in R with commented scripts, tidyverse workflows and publication quality ggplot2 output.
Explore
Data & Statistics
Machine Learning & Predictive Modelling
Classification, regression and clustering with honest validation and interpretable output.
A model that scores 98% on its training data and has never been cross-validated is not a result. Leakage, imbalanced classes and over-tuned hyperparameters produce impressive numbers that do not survive contact with new data.
We build with proper train/validation/test separation, report metrics suited to the problem rather than accuracy alone, and use SHAP or feature importance so the model can be explained.
What you receive
- Feature engineering with leakage checks
- Cross-validated model comparison
- Metrics matched to the problem (precision, recall, F1, ROC-AUC, RMSE)
- Interpretability analysis (SHAP, permutation importance)
- Deployment-ready script or notebook
Related
Others in Data & Statistics
Data Visualisation & Dashboards
Power BI, Tableau and custom dashboards built around the decisions they are meant to support.
Explore
SPSS Analysis
Descriptives through to regression, ANOVA, reliability and factor analysis — with assumption checks and APA-formatted output.
Explore
ANOVA & Hypothesis Testing
t-tests, one-way and factorial ANOVA, ANCOVA, MANOVA, repeated measures and the non-parametric equivalents.
Explore
Next step
Ready to talk about Machine Learning & Predictive Modelling?
Send the brief, the deadline and anything you already have. You will get a reference number straight away and a considered reply, usually within one working day.
- Fixed quote agreed before any work begins
- A reference number you can quote on WhatsApp
- Confidential handling, and an NDA if you want one
- An honest answer if your deadline is not realistic
