Dissertation Statistics Support, From Proposal to Defense

Your dissertation is the most significant piece of research you have ever produced, and the statistics chapter is where many strong projects stall. Committees ask pointed questions: Why this test? Did you check the assumptions? How did you handle missing data? What does this effect size actually mean?

Since 2014, I have guided master’s and doctoral candidates through exactly those questions. As a statistics professor, I know what committees and external examiners look for, and I help you build an analysis that is methodologically sound, transparently reported and, above all, yours to defend with confidence.

Who This Service Is For

• PhD, EdD, DNP, PsyD and DBA candidates writing the methodology (Chapter 3) and results (Chapter 4) chapters
• Master’s students completing a thesis or capstone with a quantitative component
• Researchers revising after committee feedback who need to rework an analysis quickly and correctly
• Mixed-methods researchers who need the quantitative strand to hold up to scrutiny

How I Support Each Stage of Your Dissertation

1. Research Questions, Hypotheses and Design

Strong analysis starts long before you open SPSS or R. We make sure each research question maps to a testable hypothesis, the right variables and the right level of measurement. I help you spot design problems early, such as confounded variables, unbalanced groups or an outcome measured on the wrong scale, while they are still easy to fix.

2. Methodology and Analysis Plan (Chapter 3)

Together we build a written analysis plan that justifies every methodological choice:

• Selecting the appropriate tests: t-tests, ANOVA/ANCOVA, MANOVA, multiple and logistic regression, hierarchical models, SEM, non-parametric alternatives and more
• Sample size and a priori power analysis using G*Power or simulation, with a citation-ready justification
• Instrument reliability and validity: Cronbach’s alpha, McDonald’s omega, exploratory and confirmatory factor analysis
• Pre-specified assumption checks and what you will do if an assumption is violated

3. Data Cleaning and Screening

Messy data is the norm, not the exception. I teach you, and document alongside you, a defensible data-preparation process:

• Coding, recoding and reverse-scoring survey items
• Diagnosing missing data patterns (MCAR, MAR, MNAR) and choosing listwise deletion, multiple imputation or FIML appropriately
• Identifying univariate and multivariate outliers (z-scores, Mahalanobis distance, Cook’s distance)
• Checking normality, linearity, homoscedasticity and multicollinearity
• Producing a clean, reproducible syntax or script file so every step can be audited

4. Running the Analysis and Interpreting Results (Chapter 4)

We work through your output line by line until you can explain it without notes. You will understand not just whether a result is “significant,” but what the effect size, confidence interval and practical significance mean for your research question. I review your results write-up for statistical accuracy and APA 7 reporting conventions, including tables, figures and the correct reporting of test statistics.

5. Discussion and Defense Preparation

The final step is confidence. In a mock-defense session, I ask the questions your committee is most likely to ask, from “Why didn’t you use a non-parametric test?” to “How would your conclusions change if that outlier were removed?”, so nothing in the room surprises you.

Software Expertise

I support dissertation analysis in SPSS, R/RStudio, Stata, Python, Excel, JASP, jamovi, AMOS, Mplus-style SEM workflows (via R’s lavaan) and G*Power. If your program or supervisor requires a specific package, we work in that package.

What Makes This Support Different

• Taught by a statistics professor, not a generalist freelancer
• Learning-first approach: you understand and own every decision in your methodology
• Committee-ready documentation: clear syntax, a cleaning log and justified methods
• Confidential by default: your data and drafts are never shared or reused
• Academic integrity built in: guidance, teaching and review that respect your institution’s policies (see the Academic Integrity Policy)

Typical Engagements

Exact scope, timeline and fees are confirmed in writing after your free consultation. See Pricing for how quotes work.

Ready to Move Your Dissertation Forward?

You do not have to figure out your statistics chapter alone. Book a free 15-minute consultation and tell me where you are in the process: your research questions, your data, your software and your deadline. You will receive a clear plan, a fixed quote and a realistic timeline, usually within 24 hours.

Request a Free Dissertation Quote →

Prefer email or chat? Write to [email protected] or message me on WhatsApp at +1 (425) 999-3993.