Thesis Statistics & Data Analysis
SPSS, R, STATA & Python analysis for your thesis or dissertation
Biostatistics consulting and statistical analysis support matched to your data and research questions — from a straightforward regression to structural equation modeling.
Methods we cover
Regression & classification
Linear and logistic regression, and related model diagnostics.
Group comparisons
ANOVA, MANOVA, ANCOVA, and chi-square analysis.
Advanced modeling
Structural equation modeling (SEM, AMOS, SmartPLS), multilevel modeling, and mixed-effects models.
Mediation & moderation
Testing indirect and conditional effects in your model.
Survival & reliability analysis
Survival analysis and reliability testing, including Cronbach's alpha and factor analysis.
Software flexibility
Work in whichever software your program requires — SPSS, R, STATA, SAS, or Python.
How it works
Share your data & questions
Your dataset and the research questions or hypotheses you're testing.
Method confirmation
We confirm the appropriate statistical approach for your data and design.
Analysis
Output tables, figures, and annotated syntax/code where relevant.
Interpretation
A plain-language write-up of what your results mean, ready for your results chapter.
Why choosing the wrong statistical test is the most common committee flag
More dissertation revisions come from a mismatched statistical test than from almost any other single issue — running an independent t-test on paired data, using Pearson correlation on non-normal data, or defaulting to ANOVA when a mixed-effects model would properly account for repeated measures. These aren't obscure mistakes; they're what committees are specifically trained to catch, because they undermine the validity of everything that follows in the results and discussion chapters.
That's why every engagement starts with method confirmation before any analysis runs — matching the test to your data's structure, distribution, and design, not just to what's fastest to compute.
Frequently asked questions
I don't know which test I need — can you help me figure that out?
Yes, that's part of the service. Share your research questions, hypotheses, and a description of your variables, and we'll confirm the appropriate method before running anything.
Do you provide the actual syntax/code, or just the output?
Both — annotated syntax or code is included so your analysis is reproducible and you can explain exactly what was run.
What if my sample size is small?
We'll flag any power or assumption-violation concerns upfront and recommend an appropriate method, including non-parametric alternatives where needed.
Related support
Dissertation Consulting
Methodology guidance and coaching alongside your statistical analysis.
See dissertation support →Meta-Analysis Services
For pooled statistical synthesis across multiple studies, rather than a single dataset.
See meta-analysis support →