Can you help with statistical analysis for a thesis or dissertation?

Yes. Projects can include method selection, data preparation, statistical modeling, diagnostics, interpretation, and explanation of the output. The final academic decisions and writing remain with the researcher.

Can you analyze my data in R, SPSS, or Python?

Yes. The analysis can be delivered in the software that fits your project or department, including R, SPSS, and Python.

Can you review an analysis that my advisor or reviewer questioned?

Yes. Existing analyses can be checked for methodological fit, assumptions, interpretation, and reporting, with the work scoped around the specific feedback.

Statistical analysis for research

Statistical analysis for your thesis, dissertation, or manuscript.

I help researchers choose defensible methods, run the analysis correctly, diagnose problems, and understand the output. Work can start from a raw dataset, an existing analysis, or reviewer feedback.

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What the service covers

From research question to defensible results

Statistical consulting works best when the method follows the research question, study design, and structure of the data.

✓

Choose the right test or model
Match the analysis to the outcome, predictors, design, and assumptions.

✓

Prepare and inspect the data
Missing values, outliers, coding issues, distributions, and data structure are checked before modeling.

✓

Run and diagnose the analysis
Results are produced in R, SPSS, or Python, with relevant diagnostics rather than output alone.

✓

Explain what the numbers mean
You receive a clear explanation of effect sizes, uncertainty, model terms, and statistical evidence.

Common requests

Projects I can help with

Thesis statisticsDissertation analysisManuscript revisionsReviewer responseRegressionANOVAMixed modelsMultivariate analysisSurvival analysisMeta-analysis

Workflow

A short, transparent process

Send the question and data

Share your research question, dataset, design, and any instructions from your advisor or reviewer.

Scope before analysis

The project is defined around the actual analytical work required. You receive the price and expected turnaround before work starts.

Analysis, output, and explanation

You receive the analysis and a written explanation that you can use to understand and communicate your own findings.

Methods

Statistical methods across common research designs

The appropriate method depends on the question and design. These are examples, not a menu that should be selected without considering the study.

Comparing groups

t-tests, ANOVA, ANCOVA, MANOVA, Mann-Whitney, Kruskal-Wallis, and chi-square tests.

Regression & modeling

Linear, logistic, Poisson, negative binomial, nonlinear, mixed-effects, and generalized models.

Multivariate analysis

PCA, cluster analysis, ordination, community-level analysis, and other multivariate approaches.

Explore the statistical methods hub →

Already have an analysis?

If you have results from SPSS, R, Python, or another workflow and want a second opinion, the project can focus on checking the analysis rather than starting over.

View the statistical analysis gig