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Academy · Concepts & Definitions · Interpreting your own analysis (workshop)
Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics
A recording of this workshop will be added once a cohort has completed it. This written session plan is intended for researchers who must interpret and report statistical analyses conducted for them by a collaborator or service.
This session is designed for researchers who have commissioned a statistical analysis from a collaborator or service and must now interpret the output and report the results accurately. It covers how to read common output formats (regression tables, forest plots, p-values and confidence intervals), how to put a clarifying question to a statistician effectively, and the common interpretation errors to check for before writing.
Learning objectives
- How to read the output that a statistician typically returns, without running the analysis.
- Which questions to ask a statistician, and how to phrase them to obtain a useful answer.
- The specific interpretation errors for which participants’ drafts are checked.
Common misconceptions
- “Researchers who cannot run an analysis themselves cannot meaningfully check its interpretation.” Interpreting statistical output correctly is a learnable skill distinct from running the analysis, and this session is designed specifically for researchers who commission rather than run statistical analyses.
Reading common statistical output formats
The session addresses the reading of a regression table (coefficient, confidence interval, p-value, and what each column represents for the specific model type), a forest plot (point estimate, confidence interval and weight; the forest plot guide provides full detail), and a results summary with multiple outcomes, distinguishing the result for the primary outcome from secondary and exploratory results.
Formulating questions for a statistician
The session covers how to frame a specific clarifying question, identifying the exact table, row or figure concerned and asking what a particular number means for the research question, rather than making a broad request such as “can you explain the statistics”, which is more difficult for the statistician to answer efficiently.
Checking drafts for common interpretation errors
Participants bring a draft results section based on an analysis they commissioned, and the session works through the common errors to check for: describing a non-significant result as “no difference” rather than “no statistically significant difference at this sample size”; treating a p-value as the probability that the null hypothesis is true; and over-interpreting the result of a secondary or exploratory outcome as confirmatory.
Session recording
A recording of a live run of this session, and the accompanying materials, will be added above once a cohort has run.
Key points
Key points
Interpreting commissioned statistics correctly is a learnable skill distinct from running the analysis. This session develops it through reading common output formats, framing specific and answerable questions for the statistician, and checking a draft against the most common interpretation errors.
Practical application
Practical application
- Frame questions to a statistician around a specific number or result rather than a general request. The question should identify the exact table, row or figure, and the research question it is intended to answer.
- Distinguish primary from secondary or exploratory outcomes explicitly in any write-up. A p-value from an exploratory analysis should not be interpreted with the same confidence as that of a pre-specified primary outcome.
- Avoid describing a non-significant result as ‘no difference’. Such a result should be described as not reaching statistical significance at the given sample size, which does not exclude the possibility of a true difference.
Frequently asked questions
No. The session focuses on interpreting output that a collaborator or service has already produced, not on running the analysis.
Both. Accurate interpretation directly informs accurate wording of the results section, so the session covers the translation of correct interpretation into correct written language.
Yes. The session is designed for researchers who commission rather than run statistical analyses, a common position for early-career principal investigators working with a biostatistics core or service.
References
- Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336(7650):924-926. read 10 October 2026. View on BMJ
Every source above is a peer-reviewed article, a publisher’s record of one, or a standard issued by the body that owns it. Each carries the date it was last read. Where a standard moves, this article is revised rather than left up with a note.
How to cite this article
Pick your referencing style and copy it. Your university or target journal may vary the punctuation — check its guide if it has one.
Pubrica Academy. (2026, October 10). Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics. Pubrica. https://pubrica.com/academy/workshop-guides/interpreting-your-own-analysis-workshop/
Pubrica Academy. “Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics.” Pubrica, 10 Oct. 2026, pubrica.com/academy/workshop-guides/interpreting-your-own-analysis-workshop/.
Pubrica Academy (2026) Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics. Pubrica. Available at: https://pubrica.com/academy/workshop-guides/interpreting-your-own-analysis-workshop/ (Accessed: 15 October 2026).
Pubrica Academy. “Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics.” Pubrica. October 10, 2026. https://pubrica.com/academy/workshop-guides/interpreting-your-own-analysis-workshop/
Pubrica Academy, ‘Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics’ (Pubrica, 10 October 2026) <https://pubrica.com/academy/workshop-guides/interpreting-your-own-analysis-workshop/> accessed 15 October 2026.
Pubrica Academy. Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics. [Internet]. Pubrica; 2026 Oct 10 [cited 2026 Oct 15]. Available from: https://pubrica.com/academy/workshop-guides/interpreting-your-own-analysis-workshop/
Pubrica Academy, “Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics,” Pubrica, Oct. 10, 2026. [Online]. Available: https://pubrica.com/academy/workshop-guides/interpreting-your-own-analysis-workshop/
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title = {Interpreting Statistical Analyses: A Workshop for Researchers Who Commission Rather Than Conduct Statistics},
howpublished = {Pubrica},
year = {2026},
month = {oct},
url = {https://pubrica.com/academy/workshop-guides/interpreting-your-own-analysis-workshop/},
note = {Accessed: <span data-cite-acc="iso">2026-10-15</span>}
}This article is written to be learned from. Cite it if you are referring to what it says; if you are using the evidence behind it, cite the sources listed above instead.
Question-framing template
For use when putting a clarifying question to a statistician.
Specific table/row/figure in question: ___ What I understand it to mean: ___ What I need to confirm or clarify: ___ Why this matters for the write-up: ___
Pubrica AcademyWritten and maintained by Pubrica’s subject matter experts. Articles are revised when the underlying standards change, and each article states the date on which it was last reviewed.
How Pubrica can help
Pubrica delivers this session for research teams that commission statistical analyses and checks draft results sections for the common interpretation errors covered here.