Overview
Running an analysis and reporting it are separate skills. Output tables contain dozens of values, and choosing the right ones, describing them correctly and formatting them to a style guide is where many theses and manuscripts lose marks or attract reviewer comments. Common problems include reporting p-values without effect sizes, describing a non-significant result as proof of no effect, and tables that repeat the text line for line.
This service starts from your research questions and your output. For each hypothesis we explain which statistic answers it, what the estimate and its confidence interval mean in the units of your study, and how certain or uncertain the result is. We then show how that is written in APA 7 notation and build tables and figures you can place in your document.
It is suitable whether we ran the analysis, you ran it yourself or a colleague did. If we notice a problem in the analysis while interpreting it, we tell you before anything is reported.
Who it’s for and the problems it solves
This is for you if you are…
- Students writing a results chapter from output they generated but do not fully understand
- Researchers preparing a manuscript for a journal that follows APA style or requires effect sizes and confidence intervals
- Authors responding to reviewers who questioned statistical reporting
- Non-native English writers who want the statistical language to be precise
Common problems we help with
- You do not know which values from a large output table belong in your results
- Your supervisor asked for effect sizes and you are not sure which one fits your test
- Tables do not follow APA 7 format, or duplicate what the text already says
- You are unsure how to describe non-significant, marginal or mixed results
- Terms like 'interaction', 'simple slopes', 'odds ratio' or 'partial eta squared' are hard to explain in words
- Reviewers commented that your reporting is incomplete or overstates causality
What’s included — and what isn’t
Included
- Hypothesis-by-hypothesis interpretation of your output in plain language
- Identification of the statistics to report for each test, with correct APA 7 notation and decimal conventions
- Selection and, where needed, calculation of effect sizes (Cohen's d, Hedges' g, η², partial η², ω², r, odds ratios, R², f²) with confidence intervals
- Guidance on describing assumption checks, corrections and exclusions
- APA 7 tables: descriptive statistics and correlations, group comparisons, regression and model comparison tables, with notes
- APA 7 figures: plots with error bars or intervals, interaction plots, and figure titles and notes in the correct format
- Guidance on wording for non-significant, unexpected and exploratory results
- Review of your drafted results section for statistical accuracy and consistency with the output
Not included
- Writing the results or discussion chapter you will submit for assessment
- Reporting only the results that support your hypotheses, or rephrasing results to imply significance that is not there
- Reanalyzing data from scratch (available through our analysis services if the original analysis needs to change)
- Guaranteeing acceptance by an examiner or journal
What you receive
- Interpretation guide
- A document that takes each hypothesis in turn, shows the relevant output values and explains what they mean and how certain they are.
- Reporting templates
- Correctly formatted example statements showing APA 7 notation for each test, using your values, which you adapt into your own prose.
- APA 7 tables
- Editable Word tables with numbered bold titles, italic titles, proper notes and consistent decimals.
- Figures
- Figures with correct numbering, titles, axis labels and notes, exported at the resolution your document needs.
- Draft review
- Comments on your written results section, checking values, notation, wording and consistency between text, tables and figures.
How it works
Send output and context
Share your research questions or hypotheses, the output files, and any draft text or style requirements.
Output check
We confirm the output matches the analysis you intended and raise any problems before interpreting.
Interpretation guide
We explain each result and identify the values to report, including effect sizes and intervals.
Tables and figures
We build APA 7 tables and figures, or format your existing ones.
Draft review and questions
After you write your section, we review it for accuracy and answer your questions.
Reporting standards and statistics we cover
- APA 7 statistical notation
- Italicized symbols (M, SD, t, F, p, r), degrees of freedom in parentheses, exact p-values to two or three decimals, p < .001 for small values, and no leading zero for statistics that cannot exceed 1.
- Effect sizes for group comparisons
- Cohen's d or Hedges' g for mean differences, η² or ω² and partial versions for ANOVA designs, with guidance on which to report for repeated-measures and factorial designs.
- Effect sizes for associations and models
- r and R² with adjusted R², standardized and unstandardized coefficients, odds ratios and incidence rate ratios with 95% confidence intervals.
- Confidence intervals
- Reporting intervals in square brackets and interpreting their width as a statement about precision, not only significance.
- Table formats
- APA 7 table structure with number, title, headings, body and notes (general, specific and probability), and horizontal rules only where needed.
- Journal Article Reporting Standards
- APA's JARS-Quant checklist for what quantitative results sections are expected to include, adapted to theses where appropriate.
From output to meaning
A result answers a question only when it is expressed in the terms of that question. 'B = 0.42, p = .003' becomes 'each additional hour of weekly tutoring was associated with a 0.42-point higher exam score, 95% CI [0.15, 0.69], holding prior attainment constant'. We help you make that translation for every hypothesis, including the units, the direction, the comparison group and the size of the uncertainty.
We also explain what a result does not show. A significant correlation in cross-sectional data is not evidence that one variable causes the other; a non-significant test is not proof that groups are equal. We suggest wording that is accurate without being evasive, and point out when an equivalence test or a Bayesian analysis would answer the 'no difference' question more directly.
Effect sizes and confidence intervals, not just p-values
The APA Publication Manual and most journals now expect an effect size and a measure of precision alongside each key test. Choosing the right effect size matters: partial η² from a factorial ANOVA is not comparable to η² from a one-way design, and Cohen's d computed from paired data can be calculated in several ways that give different values. We identify the version your design calls for, calculate it if your software did not, and explain how to describe its magnitude in the context of your field rather than relying only on generic small-medium-large labels.
- Report the estimate, its confidence interval and the exact p-value together
- State which effect size was used and how it was computed
- Interpret magnitude against previous studies or practical importance where possible
APA 7 tables and figures that do their job
In APA 7, table and figure numbers appear in bold above the element, followed by an italic title in title case on the next line. Tables use minimal horizontal lines, no vertical lines, and notes below the table for abbreviations, specific cell explanations and probability markers. Figures need clear axis labels with units, a legend only when needed, and a note if anything requires explanation.
A good table saves words: the text then highlights the key findings rather than repeating every number. We design tables around your hypotheses — for example, one regression table showing nested models side by side with ΔR² — so readers can see the argument at a glance.
Mistakes reviewers and examiners notice
Certain reporting errors recur so often that examiners look for them. We check your output and draft for each of these.
- p = .000 copied from software output instead of p < .001
- Degrees of freedom missing or inconsistent with the sample size and exclusions
- Means and standard deviations in the text that do not match the table
- Standardized and unstandardized coefficients mixed without saying which is which
- Interaction effects described without simple slopes or a plot
- Causal language ('leads to', 'improves') for correlational designs
What the work can look like
Illustrative example — fictional data
Sample interpretation note: a moderation result
A doctoral student tested whether social support moderates the relationship between workload and burnout in 286 nurses. The numbers are invented to illustrate our interpretation guides.
What the output shows
The workload × support interaction was significant, b = −0.11, SE = 0.04, t(282) = −2.75, p = .006, 95% CI [−0.19, −0.03], adding 1.9% explained variance (ΔR² = .019).
What it means
Workload is more strongly related to burnout when support is low. Simple slopes: at low support (−1 SD) b = 0.52, 95% CI [0.39, 0.65]; at high support (+1 SD) b = 0.28, 95% CI [0.15, 0.41]. Support weakens but does not remove the association.
Reporting advice
Include an interaction plot with both slopes and their confidence bands. Because the data are cross-sectional, describe support as associated with a weaker relationship rather than as protecting nurses from burnout.
Illustrative example with invented results. Your guide will be based on your own output, design and style requirements.
What you’ll need to provide
- Your research questions and hypotheses, numbered as in your document
- Complete output files (for example .spv, log files, R or Python output) rather than screenshots where possible
- A description of the design, sample and variables
- Style requirements: APA 7, a university template or journal guidelines
- Your draft results section, if you have started
You don’t need everything ready to ask for a quote — tell us what you have and we’ll say what’s missing.
What affects price and turnaround
Price depends on
- Number of hypotheses and analyses to interpret
- Complexity of the models (for example interactions, multilevel or SEM output)
- Number of tables and figures to create or reformat
- Whether a draft review is included, and the length of the draft
- Specific journal or template requirements beyond standard APA 7
Turnaround depends on
- Completeness of output files and clarity of hypotheses
- Whether analysis problems are found that need fixing before reporting
- Length of your draft and your deadline
Every project is quoted individually. How we price our work.
Questions people ask before starting
Can you interpret output from an analysis I ran myself?
Yes, that is a common request. We first check that the output reflects a sensible analysis for your design. If something needs correcting, we tell you before interpreting it.
Will you write my results section?
No. We explain your results and provide formatted tables, figures and example notation. You write the section in your own words, and we can review your draft for accuracy. This keeps your work your own and prepares you to discuss it at your defense.
My university uses a style other than APA. Can you help?
Yes. Many departments use APA-like conventions with local variations, and some fields use AMA, Harvard or journal-specific formats. Send the guide and we will follow it.
Which effect size should I report?
It depends on your test and design. We recommend the most appropriate effect size, explain how it was calculated and show how to report it with a confidence interval.
What if my results do not support my hypotheses?
That is a legitimate finding. We help you report it accurately and completely, and explain what can and cannot be concluded. We will not help present results as more supportive than they are.
Do you check consistency between my text and tables?
Yes. In the draft review we compare every reported value in your text against your tables and the original output, and flag discrepancies.