Statistical Consulting & Data Analysis
Hire a statistician for study design, analysis, and results interpretation -- reproducible R, SPSS, Stata, and SAS work behind every figure and results section we help you write.
Most statistical problems in a thesis, dissertation, or manuscript trace back to a decision made earlier than the analysis itself: a design that couldn't answer the question, a sample size that was never calculated, a test chosen because it was familiar rather than correct. We work with you from wherever your project currently stands, before data collection or after you already have a results printout you don't fully trust.
Every engagement comes with a statistician who works in your field's conventions and software, and reproducible code you keep, not a black-box output you can't explain in your own defense or peer review.
What we don’t do is fabricate or selectively report results. Every analysis reflects your actual data, run correctly and explained honestly, including when the honest answer is a null or unexpected finding.
What you get back.
Every engagement ships with concrete, reproducible artifacts, not just a conversation about your data.
Reproducible analysis code
Your full analysis in R, SPSS, Stata, or SAS, documented so it can be rerun and audited, not just a results printout.
Cleaned, documented dataset
A recoded dataset with every cleaning decision logged, ready to describe accurately in your methods section.
Publication-ready figures
Forest plots, heatmaps, survival curves, and standard charts delivered with editable source files.
Assumption & diagnostic checks
The verification work behind your test selection, documented so you can defend it under questioning.
Results write-up
Statistical output translated into results prose formatted to your journal or program’s expectations.
Reviewer-response support
Assessment of statistical critiques from reviewers or committees, with additional analysis where warranted.
Six ways to bring in statistical expertise
Hire a Statistician
When a project needs a statistician's judgment, not just software output, we assign a consultant with the right background for your design and data, whether that's a randomized trial, an observational cohort, or a survey instrument. They help you select the correct test or model, run the analysis in R, SPSS, Stata, or SAS, and write an interpretation that holds up under peer review or committee scrutiny.
Study Design & Power Analysis
Getting the design and sample size right before data collection starts is the single most consequential statistical decision in a project, and the hardest to fix retroactively. We help you choose a design suited to your research question, run the power and sample size calculations your proposal or protocol needs, and flag design issues, confounding, non-independence, ceiling effects, before they become a problem in the data.
Meta-Analysis Statistics
For reviews that pool quantitative results, we provide the statistical backbone: effect size calculation, fixed- and random-effects modeling, heterogeneity assessment (I-squared, tau-squared), subgroup and sensitivity analyses, and publication bias testing, each with reproducible code you keep.
Survey & Instrument Data Analysis
Questionnaire and Likert-scale data carries its own statistical requirements before any substantive analysis is meaningful. We handle scale validation, reliability testing (Cronbach's alpha), and exploratory or confirmatory factor analysis, then move into the substantive analysis your research questions actually call for.
Qualitative Data Analysis
For interview, focus group, and open-response data, we support thematic, framework, and grounded theory coding in NVivo, MAXQDA, or ATLAS.ti, with a documented codebook and audit trail so your coding decisions are defensible and your inter-rater reliability is demonstrable where required.
Dissertation Statistics Support
Results chapters have to do two things at once: run the correct analysis and explain why it's correct, including the assumption checks a committee will ask about. We help you justify your test selection, verify assumptions, run the analysis, and write results prose that anticipates the methodological questions a defense will raise.
The work underneath the results section
Data Cleaning & Recoding
Messy data, missing values, inconsistent coding, outliers, has to be resolved with a documented, defensible process before analysis, not fixed invisibly along the way. We clean and recode your dataset with a clear record of every decision, so your methods section can describe exactly what was done and why.
Statistical Software Analysis
We run analyses directly in R, SPSS, Stata, or SAS, whichever your program or field expects, and hand back reproducible code alongside the output, not just a results printout you can't audit or rerun yourself.
Regression & Multivariate Modeling
From linear and logistic regression through mixed-effects models, survival analysis, and structural equation modeling, we help you select and fit the model that actually matches your data structure and research question, and check the diagnostics that confirm it's appropriate.
Reliability & Validity Testing
Before a measure or scale can carry the weight of your analysis, its reliability and validity need to be established and reported, not assumed. We run the internal consistency, test-retest, and construct validity checks your methodology needs to be taken seriously.
Turning output into a defensible results section
Data Visualization & Figures
Publication-quality figures, forest plots, heatmaps, survival curves, and standard charts, built in ggplot2, Python, or GraphPad Prism, delivered with editable source files so you can adjust them yourself later without starting over.
Results Write-Up
We help you translate statistical output into results prose that reports what's required, effect sizes, confidence intervals, test statistics, in the format your journal or program expects, without overstating or underexplaining what the numbers show.
Reviewer Query Resolution
When a peer reviewer or committee member raises a statistical objection, methodology, model choice, an alternative test they'd expected, we help you assess whether the critique is valid and draft a response, additional analysis included where genuinely warranted.
Committee & Defense Preparation
Before a proposal or dissertation defense, we walk through the statistical decisions in your study with you, the ones most likely to draw committee questions, so you can explain and defend your analysis choices in your own words, not read from a script.
Statistical Report Editing
A line-by-line check of your methods and results sections against your actual analysis, catching mismatches between what you ran and what you reported, a common and avoidable source of reviewer pushback.