Statistics reports are frequently penalised for two things: presenting output from R or Python without interpreting it, and failing to check or discuss model assumptions. A regression report that includes diagnostic plots without commenting on what they show, or worse, includes plots that reveal assumption violations without acknowledging them, loses marks at every grade level.
Our statistics mentors hold MSc and PhD degrees from statistics departments including Imperial, Warwick, Bath, and Southampton. Their research backgrounds span Bayesian statistics, biostatistics, machine learning methods, and statistical consulting.
We support data analysis write-ups, regression and time series reports, Bayesian analysis documentation, research methodology sections, and dissertation chapters for statistics, biostatistics, and data science programmes.
Modules we cover
Sample essay topics we've supported
- Comparing maximum likelihood and Bayesian estimation for a Poisson regression model
- Bootstrapping and its applications in situations where distributional assumptions fail
- ARIMA modelling of inflation data: model selection and diagnostic checking
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