Services / Dissertation statistics help
Dissertation statistics help, explained so you can defend it
You have collected the data. You need the analysis to be right, and you need to understand it well enough to answer questions about it. A named statistician runs the tests, annotates the output and talks you through what it means.
- Correct test chosen and justified
- Annotated output you can follow
- Reusable syntax for your appendix
- A walkthrough before your viva
Dissertation statistics help is support from a qualified statistician who analyses data you have already collected and explains the results. It covers choosing and justifying the right test, checking assumptions, producing annotated output and APA tables, and preparing you to defend the findings in a viva. The written work remains yours.
What is included
What you get with dissertation statistics help
The right test, justified
Chosen for your design, your variables and your sample — with a written reason you can give your supervisor.
Assumptions checked properly
Normality, homogeneity, independence. Where an assumption fails we use the appropriate alternative and say so.
Annotated output
Every table labelled, so you know which number answers which research question.
APA-ready tables
Formatted to your university's requirements, ready to drop into the chapter you write.
A plain-English reading
What the result means in words, so you can say it out loud under questioning.
Viva preparation
The questions an examiner is most likely to ask about your analysis, and how to answer them.
Who it is for
Two kinds of client, one standard of work
- A dissertation dataset that needs analysing correctly
- Uncertainty about which test your design requires
- SPSS output you cannot interpret confidently
- A deadline that is closer than you would like
- Multi-variable models and complex designs
- Analysis that has to withstand a viva
- A supervisor who has queried your method
- Preparing results for publication as well as submission
Choosing the analysis
Which statistical test does your data actually need?
Nearly every enquiry starts with a version of this question. The answer turns on three things: what kind of outcome variable you have, how many groups or measurements you are comparing, and whether the same participants appear in more than one condition.
| Your design | Continuous outcome | Categorical outcome |
|---|---|---|
| Two independent groups | Independent samples t-test, or Mann-Whitney U if normality fails | Chi-square test of independence, or Fisher’s exact for small cells |
| Two measurements, same people | Paired samples t-test, or Wilcoxon signed-rank | McNemar’s test |
| Three or more independent groups | One-way ANOVA, or Kruskal-Wallis | Chi-square across categories |
| Repeated measures over time | Repeated measures ANOVA, or a mixed model where data is missing | Generalised estimating equations |
| Relationship between two variables | Pearson correlation, or Spearman for ranked or skewed data | Cramér’s V |
| Predicting from several variables | Multiple linear regression | Binary or multinomial logistic regression |
Sample size, distribution, the level at which your data is clustered, and whether observations are genuinely independent all change the recommendation. That is why the written justification matters more than the name of the test.
Surviving scrutiny
What your supervisor and examiner will check
Examiners rarely question whether you ran a t-test correctly. They question the decisions around it — and they do so in a predictable order.
Were assumptions checked?
Normality, homogeneity of variance, independence, linearity, multicollinearity. The check takes minutes; omitting it is what costs marks.
Does the test match the methods?
A surprising number of chapters describe one design in the methods and analyse another in the results. That is an immediate flag.
Are claims proportionate?
A p-value says an effect is unlikely to be zero. It does not say it is large, important, or causal.
Do text and tables agree?
Mismatches between prose and tables are among the most commonly issued corrections, and are entirely avoidable.
Is the effect size reported?
Reporting effect size alongside significance both strengthens the chapter and pre-empts the obvious question.
Can you explain it aloud?
Everything above is examinable in a viva. If you cannot say it in your own words, the analysis is not finished.
Before analysis starts
Problems we see most often in dissertation datasets
It is normal for a dataset to need work before any test is run. None of these mean your project is in trouble — all of them are cheaper to fix now than after the analysis.
Where a problem cannot be fixed, we tell you what it means for the claims you can make and help you write the limitation honestly. A limitations section naming a real constraint reads far better than one listing generic caveats.
SPSS, R, Stata and the rest
Software, and what you actually receive
We work in SPSS, R, Stata, Python, Mplus, AMOS and SmartPLS. If your department requires a particular package — many do, either for teaching or because your supervisor wants to open the file — say so and we will use it.
Output only
- No record of what was actually done
- Cannot be checked by a reviewer or examiner
- One added variable means starting again
- Impossible to correct an error six weeks later
Output plus syntax
- Every step recorded and reproducible
- A supervisor can verify the analysis directly
- Adding a variable takes minutes
- Corrections are a small edit, not a restart
You also receive the output annotated table by table, tables formatted to APA or your department’s convention, and a plain-English explanation written so you can say it in your own words.
Viva and supervision
Preparing for questions about your analysis
The point of the explanation is that you can defend the work without us. Examiners ask a narrow and fairly predictable set of statistical questions, and knowing them in advance is most of the preparation.
We go through these against your actual results before your viva at no additional cost. If you cannot answer a question about your own analysis, the job is not finished.
How it works
Three steps, entirely in writing
Send what you have
Attach the data, or just describe the project. No account, no mandatory call, and a five-field form rather than a fifteen-field one.
Approve a fixed quote
Usually within one working day, naming the statistician assigned, the deliverables and the deadline.
Receive the work
Output, syntax and a plain-English explanation — with follow-up questions answered at no extra cost.
Client feedback
What clients say about this work
“The statistician explained every test clearly and helped me understand my dissertation results. Everything was completed before my deadline.”
“Excellent support with my dissertation analysis. The results chapter became much stronger after their statistical guidance.”
Proof
This work, on real projects
Clients are not named and no identifying detail is published, so what is described is the statistical problem — which is the part that shows whether a consultancy knows what it is doing.
Multilevel Modelling of Student Performance Across Twenty Departments
Accounting for students clustered within courses and departments, where ignoring the hierarchy would have manufactured significance.
Third sector · Factor analysis and ordinal regressionExploratory Factor Analysis and Ordinal Regression on a National Survey
Reducing 75 overlapping questionnaire items to interpretable factors, then modelling an ordinal outcome correctly.
Life sciences · Linear mixed effects modelsLinear Mixed Effects Models for an Intervention Measured Over Six Occasions
Recovering a defensible effect estimate from repeated measures with missing follow-up, where repeated measures ANOVA could not be used.
Your statistician
Who does this work
Member of the Royal Statistical Society
Experimental design, survival analysis and Bayesian methods across medicine, psychology, public health and engineering.
This page was reviewed for statistical accuracy by Hafiz Ahmad Tariq on 14 August 2026.
Common questions
Answers before you ask
Will you write my dissertation?
No. We analyse the data and explain the results; the writing is yours. That boundary is what makes the support usable — and it is also what your examiner expects.
Will my university be happy with this?
Yes. Statistical support is standard practice and permitted at every UK university we have worked with. If your institution asks you to declare the support you received, we will give you a written description of exactly what we did.
What software do you use?
SPSS, R, Stata, Python, Mplus, AMOS and SmartPLS. If your department requires a particular package, say so and we will use it.
What if I do not understand the output?
Then the job is not finished. Explanation is part of the price, and follow-up questions after delivery are included.
How fast can you turn it around?
Quotes usually go out within one working day. The analysis itself depends on the dataset, and the deadline is agreed in writing before you commit.
Related
Often needed alongside this
SPSS data analysis
The right tests, annotated output, reusable syntax and APA-ready tables.
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A statistician checks the chapter you wrote before it is submitted.
Fixed quotePower analysis & sample size
A priori power analysis with the justification an ethics committee will accept.
From £180Send the data. Get a fixed quote.
Attach your dataset or just describe the project. A named statistician replies with a price and a deadline, usually within one working day.