Client desk

Rigorous statistics. Persuasive writing. One trusted desk.

DataQuill supports researchers, universities, companies and NGOs with analysis you can defend in peer review, and proposals and grants built to be funded.

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Analysis and writing for agriculture, environment and health research

From a single dataset to a multi-year programme, each engagement is built around your question, your data and your deadline.

01

Statistical and scientific analysis

Experimental and observational data in biology, agriculture, health, environment, social science and engineering. Design, cleaning, modelling, diagnostics and publication-ready tables and figures.

02

Meta-analysis and systematic reviews

Protocol design, search and screening support, effect-size extraction, random-effects models, heterogeneity, publication-bias tests and PRISMA-compliant reporting.

03

Geospatial analysis

Mapping, spatial statistics and remote-sensing workflows for field sites, land use, climate exposure, pest and disease spread, and service coverage. Clear maps your reviewers and funders can read.

04

A/B testing for shops and businesses

Test pricing, layouts, promotions and campaigns with sound sample sizes and honest results. You learn what truly moves sales, not what looked good for a week.

05

Machine learning, built to scale

Small, well-validated models for companies and NGOs: forecasting, classification, segmentation and risk scoring. Right-sized, explainable and handed over with documentation your team can maintain.

06

Scientific writing and editing

Manuscripts, methods and results sections, and statistical reporting for researchers preparing work for publication, written to your target journal's style, with our contribution acknowledged as journals require. For students, we offer review, editing, statistical guidance and defense preparation; you remain the author of your thesis.

07

Proposal and grant writing

Concept notes, research proposals and full grant applications for organisations, NGOs, companies and research teams, with a clear problem, a credible design, a defensible analysis plan and a budget that matches the work.

08

Statistical consulting for students

One-to-one guidance on study design, choosing and running the right analysis, interpreting output, and preparing for your defense. We teach and review; we do not write assessed work.

A statistical foundation you can cite

Every analysis is chosen for the structure of your data, checked against its assumptions, and reported so another researcher could reproduce it.

Inference and modelling

ANOVA and designed experiments, linear and generalised linear models, mixed-effects models, survival analysis, Bayesian methods, power and sample-size planning.

Multivariate and spatial

Ordination, clustering, dimension reduction, time series, spatial interpolation, species and habitat modelling, and geostatistics.

Evidence and prediction

Meta-regression, sequential and Bayesian A/B testing, cross-validated machine learning, model calibration and interpretable outputs.

  • Python
  • R
  • SPSS
  • Power BI
  • KNIME
  • Tableau
  • SQL
  • QGIS

Scripts, workflows and data dictionaries are delivered with each project, so every result can be traced and rerun.

How we work together

  1. BriefShare your question, data and deadline. A short call or message is enough.
  2. Scope and quoteYou receive a clear plan, timeline and fixed price before any work starts.
  3. Analysis and draftingWork proceeds with checkpoints, so you see progress and can steer it.
  4. DeliveryFinal report, methods text, figures and reproducible code, with revision support.

Selected work

A sample of reports, figures and deliverables from past projects, shared with client permission.

WOWycliff Obara, lead analyst at DataQuill

Led by a researcher who works with data every day

DataQuill is led by Wycliff Obara, a data scientist and agricultural researcher with over five years of experience in research, designing studies, leading field teams and turning complex data into decisions.

His work spans national programmes that registered and trained hundreds of thousands of smallholder farmers, laboratory and field trials, and analytics dashboards for policy makers. He writes and analyses with a working researcher's understanding of what reviewers, supervisors and funders look for.

Experience and professional certifications

Field-tested across national programmes, research trials and analytics projects, and backed by more than 70 completed professional courses.

190,000+farmer registrations supported through digital data collection
200,000+smallholder farmers reached through training programmes
5+ yearsin research, field operations and data science
70+professional certifications in data, AI, project management and agriculture

Data science and analytics

Certified in data analysis with R and SQL, data engineering and applied statistics in Python, and statistical inference in R. Trained in machine learning and cloud data fundamentals, and in the tools clients already use: Tableau, KNIME and SPSS.

AI, quality and finance

Foundations and ethics of artificial intelligence, applied responsibly in research workflows. Quality and problem-solving methods including Lean Six Sigma, 8D and 5W2H, and financial modelling and valuation for project budgets and business cases.

Programmes and development

Project management for humanitarian and development programmes, and Agile delivery. Specialist training in digital agriculture, climate-smart agriculture, sustainable development and gender-inclusive agricultural productivity.

Integrity policy

DataQuill supports research integrity. We do not complete assignments, theses or other assessed work for students to submit as their own. Writing support for publications is disclosed in line with journal and ICMJE guidance.

Bring us your data, your draft or your idea

Tell us what you are working on and when it is due. You will receive a clear reply and a proposed plan.

help@dataquill.it.com