Data Analysis & Interpretation
Statistical Analysis You Can Actually Defend
The right test for your design, run properly, with results written up in language you can explain to a supervisor, a board or a client.
- SPSS · R · Stata · Python
- Assumption checks included
- Plain-language interpretation
- Publication-ready tables
- Survey design and validation
- Reproducible workflow
Tell us about your data
Share a few details and we’ll come back with a tailored plan.
Every project is confidential — NDAs available on request.
What’s included
Analysis done properly, explained plainly
Descriptive and inferential statistics
The groundwork done properly, with assumptions tested rather than quietly assumed.
Regression, ANOVA, SEM and factor analysis
The model matched to your design and your research question, not to convenience.
SPSS, R, Stata and Python workflows
Whichever tool your institution or team requires, with the syntax handed over to you.
Survey design and validation
Instruments built to measure what you intend, with reliability and validity checked.
Charts, tables and visual reporting
Outputs formatted for publication or presentation, not raw software dumps.
Written interpretation of results
What the numbers mean, what they don't mean, and where the limitations sit.
How it works
Four steps, no surprises
Share your data and design
Send your dataset or study design, plus the questions you need answered.
Get a tailored plan
Recommended methods, timeline and a fixed quote before anything is run.
Analysis and review
Results delivered with the reasoning explained, and revisions where you need them.
Final handover
Outputs, tables, syntax files and a written interpretation you can defend.
Not sure which test you need?
Send us your design and we'll tell you what your data can actually support. Your first 15 minutes are free, with no obligation.
From our blog
- HTMT discriminant validity: is the threshold 0.85 or 0.90?Both — and since 2019 the test itself has changed. The cutoffs, the bootstrap procedure, and the exact SmartPLS 4 steps.
- How to calculate sample size for PLS-SEM using G*PowerWhy the 10 times rule fails, the exact G*Power settings, and a lookup table by predictors and effect size.