Overview
Quantitative results chapters are often weakened by pasted software output, missing effect sizes, inconsistent decimal places, or tables that repeat the text. Qualitative findings chapters more often struggle with themes that are really topics, quotations without analysis, or an imbalance between participants. In both, a frequent examiner comment is that results and discussion are blurred, or that the chapter does not map back to the research questions.
We review your chapter against your questions, your methodology and the reporting conventions of your field, such as APA 7 for many social sciences. We check that each finding is reported completely and accurately, that tables and figures are clear and necessary, and that interpretation is proportionate. If your program combines results and discussion, we check that the two functions remain distinguishable.
You produce the analysis (or received it from an analyst) and write the chapter; we give feedback so the reporting is accurate and readable.
Who it’s for and the problems it solves
This is for you if you are…
- Quantitative researchers turning SPSS, Stata, R or SmartPLS output into a results chapter
- Qualitative researchers presenting themes, categories or a grounded theory model
- Mixed-methods researchers reporting and integrating both strands
- Students whose supervisor has said the results are "hard to follow" or "over-interpreted"
- Candidates checking results reporting before submission or after examiner comments
Common problems we help with
- Your chapter contains raw software output rather than formatted tables
- You are unsure which statistics to report (effect sizes, confidence intervals, exact p-values)
- Themes are described but not evidenced, or quotations are left to speak for themselves
- Results are not organized by research question or hypothesis
- Interpretation and discussion have crept into the results chapter, or the reverse
What’s included — and what isn’t
Included
- Checking structure: preliminary analyses, then results by question or hypothesis, then summary
- Accuracy of statistical reporting: test statistics, degrees of freedom, exact p-values, effect sizes and confidence intervals
- Reporting of assumption checks, missing data handling and sample characteristics
- Table and figure review: necessity, numbering, titles, notes, units and consistency with your style guide
- For qualitative work: theme structure, definitions, balance of evidence, use of quotations and analytic commentary
- For mixed methods: joint displays and how integration is shown
- Checking consistency between the text, tables, figures and appendices
- Feedback on how far interpretation belongs in this chapter versus the discussion
Not included
- Running or rerunning the statistical or qualitative analysis within this service
- Writing the results chapter for you
- Altering, selecting or omitting results to make findings look stronger
- Guaranteeing that a particular result will satisfy examiners
What you receive
- Reporting accuracy check
- A list of any statistics, values or labels that appear inconsistent or incomplete, cross-checked against the output you provide.
- Table and figure feedback
- Comments on each table and figure with suggestions for layout, labels and notes according to your style guide.
- Annotated chapter
- Tracked comments on structure, clarity, completeness and interpretation.
- Question-to-result map
- A table showing where each research question or hypothesis is answered, flagging any that are unanswered or only partly addressed.
How it works
Collect materials
You share the chapter, research questions, output files or coding framework, and style guide.
Accuracy and structure review
We cross-check reported values and assess structure and mapping to questions.
Detailed feedback
You receive annotated comments, table feedback and the question-to-result map.
Follow-up
We answer questions about the feedback and review a revised version if included in scope.
Reporting conventions we check
- APA 7 statistical reporting
- Italicized statistical symbols, exact p-values to two or three decimals, effect sizes such as Cohen's d, partial eta squared or R², and confidence intervals where appropriate.
- Descriptive and preliminary analyses
- Sample characteristics, missing data, reliability of scales and assumption checks reported before inferential tests.
- Table and figure design
- Tables for precise values, figures for patterns; no duplication of the same information in both.
- Qualitative findings
- Theme names that make a claim, definitions, prevalence described cautiously, and quotations embedded in analytic commentary.
- Mixed-methods integration
- Joint displays, side-by-side comparison or following a thread, depending on the design.
Results versus discussion
In most quantitative dissertations, the results chapter reports what was found and briefly states whether each hypothesis is supported; the discussion interprets why and compares with literature. In many qualitative dissertations, findings and interpretation are more intertwined, and some programs combine the chapters. We help you apply the convention your program expects without mixing roles accidentally.
What a complete statistical result looks like
Reporting only a p-value tells the reader that an effect is unlikely to be zero, not how large or precise it is. Examiners increasingly expect effect sizes and confidence intervals alongside significance tests, and a clear statement of the direction of the effect. We check each reported result for these elements and for internal consistency, such as degrees of freedom that match your sample.
- Test and statistic with degrees of freedom
- Exact p-value (rather than only "p < .05")
- Effect size with interpretation appropriate to the field
- Confidence interval where the method provides one
- Plain-language statement of what the result means for the hypothesis
Presenting qualitative findings convincingly
Strong findings chapters name themes as insights ("Carers negotiate a hidden workload") rather than topics ("Workload"), show how each theme is built from the data, and use quotations to illustrate analytic points rather than to replace them. We also check that a few articulate participants are not over-represented and that contradictory cases are acknowledged.
What the work can look like
Illustrative example — fictional data
Illustrative example: reporting a regression result
A fictional MSc psychology student reported: "Social support was significant (p = .000)." The values below are invented to illustrate the feedback.
Issues flagged
"p = .000" is not a valid exact value; the coefficient, its direction, confidence interval and the model's explained variance were missing; and the table repeated every number in the text.
Suggested reporting pattern
Perceived social support predicted lower loneliness, b = −0.42, 95% CI [−0.58, −0.26], p < .001, with the model explaining 21% of variance (R² = .21). The student then trimmed the text and let the table hold the full coefficients.
Mapping
The result was placed under the heading for Hypothesis 2 so examiners could locate it directly.
Illustrative example with invented numbers and a fictional student. It shows the kind of feedback provided, not real results.
What you’ll need to provide
- Your results or findings chapter draft
- Research questions and hypotheses
- Statistical output files or, for qualitative work, your codebook or theme table
- Your methodology chapter or a summary of the analysis plan
- Required style guide or university template
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
- Chapter length and number of analyses, tables and figures
- Whether output must be cross-checked value by value
- Quantitative, qualitative or mixed-methods reporting
- Number of review rounds
Turnaround depends on
- Availability of output files and codebooks
- Number of tables and figures
- Your submission or committee deadline
Every project is quoted individually. How we price our work.
Questions people ask before starting
Can you interpret my results for me?
We explain what your results mean statistically so you understand them, and we check whether your interpretation is accurate. You write the interpretation in your own words, which also prepares you for questions in your viva or defense.
I haven't run my analysis yet. Is this the right service?
Not yet. Our data analysis services cover running and explaining the analysis. Come back for chapter feedback once you have results.
Which style guide do you follow?
The one your program requires. APA 7 is common in social sciences and health; other fields use their own conventions or a university template.
Should I put all my output in the appendix?
Usually not all of it. Appendices should hold supporting material your examiners may need, such as full tables or instruments, not every page of output. Check your program's guidance.
Can you check results produced by another analyst?
Yes. We review how the results are reported in your chapter. If you want the analysis itself audited, our results interpretation and reproducibility services cover that.