The wrong test for the question
Running correlations when the hypothesis is about differences, or t-tests when there are more than two groups. Each research question needs a test that matches it.
Master's & MBA statistics help · South Africa
From survey data to a results chapter you can defend
Statistics help for Master's dissertations and MBA research reports: the right tests, clean analysis, report-ready tables and clear explanations, on a timeline that fits around your job. Led by Dr Michael Pietersen (PhD, University of Pretoria).
- ✓ Risk Reviews from R4,000
- ✓ Analysis from R9,500
- ✓ SPSS, R, SmartPLS-style outputs
- ✓ No ghostwriting
Supporting candidates from leading institutions: WBS, GIBS, UCT GSB, Stellenbosch, Henley, Milpark, UNISA SBL
Why candidates get in touch
Where Master's and MBA analysis usually goes wrong
Most problems in a research report are not about the software. They come from choosing the wrong test, skipping the checks examiners expect, or misreading what the output says.
Scales used without checking them
Averaging Likert items into a score without confirming reliability and, where needed, factor structure. Examiners expect Cronbach’s alpha or omega at a minimum.
Assumptions not reported
Normality, outliers, multicollinearity and heteroscedasticity left unchecked or unreported. A short, honest assumptions section prevents a lot of questions.
Moderation and mediation done by hand
Interaction terms without centring or simple-slopes analysis, and indirect effects tested with outdated methods instead of bootstrapped confidence intervals.
Significance without meaning
Reporting p-values without effect sizes or practical interpretation. A significant result is not automatically an important one.
Questionnaire problems found too late
Ambiguous items, missing constructs or too small a sample discovered after data collection, when they are expensive to fix.
How we help
Help with your dissertation or research report analysis
You can bring us in at proposal stage, after data collection, or when supervisor feedback arrives.
Before data collection
Questionnaire and scale review, sample size, and an analysis plan that matches your research questions and hypotheses.
Data preparation
Cleaning and coding survey data, handling missing values and reverse-scored items, and building composite scores.
Analysis
Reliability, factor analysis, regression, ANOVA, moderation and mediation, PLS-SEM or SEM, with full diagnostics.
Reporting and revisions
APA- or Harvard-ready tables, interpretation notes in plain English, and support through supervisor feedback.
Methods we support
Survey analysis
- Descriptive statistics
- Reliability (alpha and omega)
- Exploratory and confirmatory factor analysis
- Composite scores and reverse coding
Testing relationships
- Correlation and multiple regression
- Hierarchical regression
- Logistic regression
- Moderation and mediation (bootstrapped)
Comparing groups
- t-tests and ANOVA
- Chi-square tests
- Non-parametric alternatives
- Effect sizes and post-hoc tests
Models and software
- PLS-SEM and covariance-based SEM
- Panel regression for finance studies
- SPSS and AMOS conventions
- R, Python and SmartPLS-style reporting
The standard of work
What you actually receive
Tables formatted for your results chapter, the checks your supervisor will ask about, and notes that explain what each number means. Below is an excerpt in the format we deliver.
Example uses a synthetic topic and simulated data. It is not client work.
Example table
Does supervisor support change how remote work relates to job satisfaction?
| Step 3 predictors | b | SE | p |
|---|---|---|---|
| Age | 0.04 | 0.05 | .38 |
| Tenure | 0.07 | 0.05 | .16 |
| Remote work intensity | −0.08 | 0.05 | .11 |
| Supervisor support | 0.39 | 0.05 | <.001 |
| Remote work × Support | 0.13 | 0.047 | .006 |
| R² by step (1 / 2 / 3) | .04 / .21 / .23 | ||
| ΔR² for the interaction | .02, F(1, 294) = 7.64, p = .006 | ||
N = 300. Predictors standardised before forming the interaction term.
Example table
Scale reliability
| Scale | Items | α | ω |
|---|---|---|---|
| Remote work intensity | 4 | .84 | .85 |
| Supervisor support | 6 | .91 | .91 |
| Job satisfaction | 5 | .88 | .89 |
Interpretation note
Supervisor support moderates the relationship between remote work intensity and job satisfaction (b = 0.13, p = .006). Simple-slopes analysis shows that remote work is associated with lower satisfaction when support is low (−1 SD: b = −0.21, p = .002), but not when support is high (+1 SD: b = 0.05, p = .44).
What it means in practice
The interaction explains an extra 2% of variance. That is modest, but moderation effects in survey research are usually small. The practical message is about who is affected: employees with weak supervisor support are the ones whose satisfaction drops as remote work increases.
Anticipated supervisor question
“Why standardise before creating the interaction?” Answer prepared: it makes the main effects interpretable at average levels of the other variable and reduces non-essential collinearity. It does not change the test of the interaction itself.
Recent engagements (anonymised)
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MBA survey research
Questionnaire weaknesses identified before analysis, then a full statistical analysis the candidate could defend.
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Master of Medicine
An iterative statistical methods review for a survey study on clinical practice behaviour.
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MPhil forecasting study
A focused statistical review of a completed forecasting model built on online search data.
Client feedback
What researchers say about working with us
★★★★★
“I appreciated the detailed and in-depth engagement [from Michael]. [Michael] didn't just run the statistical analysis for me, [he] handled everything with such care that I had complete confidence in the results. What really stood out for me though was how [he] caught a few critical weaknesses in my survey. Not only did [he] flag the issues, but [he] also identified possible solutions that I would've never considered. I would recommend [him] without hesitation to anyone doing high-level postgraduate research.”
Aaron
Master of Business Administration, SBS
★★★★★
“I really appreciated the guidance [Michael] provided on the steps I needed to take to ensure that I present and communicate my research and results properly. No amount of reading prepared me for the complexity of what I had to do. I appreciated the assistance in showing me how to set everything up for success.”
“At proposal stage, if you are in doubt about quantitative analysis or mixed-methods, Michael is able to guide you to make the right decision. The research methodology you choose will support a high-performance dissertation and may have a meaningful impact on your future career.”
Deborah
Master’s in Organisational Psychology, UNICAF
★★★★★
“[The support I found most useful was] the structured, continuous engagement to work through each milestone, and the explanations of why certain methods do or don't work. I learnt, for example, how the GMM model and imputation work. I found StatForge to be highly thorough and rigorous in first developing a strategy for the testing methods.”
Anonymous
Postgraduate researcher (name withheld at client's request)
Who does the work
Dr Michael Pietersen
Every engagement is led personally by Dr Pietersen, a quantitative researcher who has been through doctoral examination himself. Your analysis is never passed on to a junior analyst.
View publications on Google Scholar-
PhD, University of Pretoria
Doctorate completed in 2022, with a strong quantitative focus. MPhil awarded cum laude.
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Peer-reviewed researcher
Four peer-reviewed publications, two of them in ABDC A-rated journals.
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Advanced methods
SEM/CFA, PLS-SEM, panel data and GMM, ARDL and GARCH, fsQCA, and applied machine learning.
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Reproducible by default
Analysis in documented R or Python code, so every number in your thesis can be traced and re-run.
Transparent pricing
How much does Master's or MBA statistics help cost?
Fixed scope and price agreed before any work starts.
Research Design & Analysis Risk Review
R4,000–R8,500
A senior review of your design, questionnaire or data before you invest in full analysis.
- ✓Pre-read of your proposal and data description
- ✓60–90 minute structured call
- ✓Test selection and sample size check
- ✓Written memo with risks, fixes and next steps
Most chosen
Analysis Execution
From R9,500
The full analysis for a typical Master’s dissertation or MBA research report.
- ✓Data cleaning and coding
- ✓Reliability and assumption checks
- ✓Analyses matched to each research question
- ✓Report-ready tables, code and interpretation notes
- ✓Support for supervisor feedback
Extensions & Revisions
From R3,500
When you already have results but need changes or additional tests.
- ✓Model refinement and re-specification
- ✓Additional variables, interactions or tests
- ✓Updated tables and figures
- ✓Supervisor feedback response support
Complex models such as covariance-based SEM with invariance testing, or panel GMM, are quoted under Research Pro from R20,000.
How it works
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1
Free 15-minute scoping call
You share your proposal, questionnaire or data, and your deadline.
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2
Fixed scope and quote
You receive the deliverables, timeline and price before any work starts.
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3
Analysis
Usually one to two weeks once the data is ready, delivered with clear explanations.
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4
Handover and revisions
Tables, code and interpretation notes, plus support when supervisor feedback arrives.
Ethical support, clearly defined
We do
- ✓ Advise on design and tests
- ✓ Prepare data and run analyses
- ✓ Deliver tables, figures and code
- ✓ Explain results so you can defend them
We don't
- ✗ Write chapters or ghostwrite
- ✗ Fabricate or manipulate data
- ✗ Make your interpretive decisions
- ✗ Submit work on your behalf
Your data and drafts are treated as confidential and used only for your project.
Request a quote for your analysis
Tell us about your study and deadline. You'll receive a recommended scope, deliverables, timeline and price.
Master's and MBA statistics help: frequently asked questions
Can you help me analyse my survey data in SPSS?
Yes. We clean and code your survey data, check scale reliability, run the tests your research questions require and deliver report-ready tables. Analyses are run in R or Python for reproducibility and aligned with SPSS output conventions, or delivered as SPSS-compatible output where your programme requires it.
Will you write my results chapter?
No. We deliver the analysis, APA- or Harvard-ready tables and figures, and interpretation notes that explain what each result means and how examiners are likely to read it. You write the chapter in your own words. This keeps the work ethical and ensures you can defend it.
How much does Master's or MBA statistics help cost?
A Risk Review of your design and data costs R4,000–R8,500. Analysis Execution, which covers most Master's and MBA research reports, starts at R9,500. If you already have results and need supervisor-requested changes, Extensions & Revisions start at R3,500.
My deadline is close. How quickly can you help?
Analysis Execution usually takes one to two weeks once the data is ready. Rush work within 48–72 hours is possible for tightly scoped tasks when capacity allows, so tell us your deadline when you get in touch.
Can you check my questionnaire before I collect data?
Yes, and it is the best time to involve us. A Risk Review at proposal stage catches problems with constructs, scales, sample size and planned tests while they are still cheap to fix.
My supervisor wants PLS-SEM or SmartPLS. Can you help?
Yes. We run PLS-SEM with established packages such as SEMinR or cSEM and report it in the format SmartPLS users and examiners expect, including reliability, convergent and discriminant validity, and bootstrapped path estimates.
I'm a working professional. How does the process work?
Most MBA candidates are. You share your proposal and data, we agree a fixed scope and timeline after a short call, and the work is delivered in clear stages that fit around your job. Calls are online and scheduled at times that suit you.
Doing a PhD or DBA? See PhD statistics help →