As strongly as your design allows and no more. A descriptive survey lets you say what your respondents reported. A correlational study lets you say two things move together. Neither lets you say one causes the other, and neither lets you say anything about Nigerians in general. The verb and the modal you choose are where that boundary is either respected or crossed.
Panels rarely attack a finding. They attack the sentence the finding was written into. Every answer below stands on its own and can be applied to a single sentence of your Chapter Five without reading the rest of the page.
What is the difference between a finding and a claim?
A finding is what your data shows. A claim is what you say that means. “The respondents obtained a mean score of 3.42 on the training subscale” is a finding — it is a fact about 300 people who filled a questionnaire. “Training improves employee productivity in Nigerian banks” is a claim, and it is about an entire industry you did not sample.
Everything in this article is about the distance between those two sentences, and about the words that either bridge it honestly or hide it.
How strong a claim does each design license?
| Your design | You may write | You may not write |
|---|---|---|
| Descriptive survey | “The respondents rated the practice high (mean = 3.42).” | “Nigerian workers rate the practice high.” |
| Correlational | “A significant positive relationship was found between the two variables (r = .48, p < .05).” | “Training increases productivity.” |
| Causal-comparative | “Respondents in the trained group reported higher scores than those in the untrained group.” | “Training caused the difference.” |
| Quasi-experimental | “The intervention was associated with a significant improvement in the treatment group.” | “This proves the intervention works.” |
| Case study of one firm | “In the organisation studied, three themes emerged.” | “Nigerian firms typically show three patterns.” |
The right-hand column contains the sentences that end up in Chapter Five. Which design you are actually working with, and which test goes with it, is covered in the guide to choosing a statistical test for your project.
What does a Taro Yamane sample of 300 actually let you say?
It lets you say something about the population you drew the 300 from, and nothing about any other population. If your Taro Yamane calculation started from a staff list of 1,200 employees of one organisation, your findings are about that organisation. Not about the sector, not about the state, and certainly not about Nigeria.
This is worth being blunt about, because the formula creates a false sense of reach. Taro Yamane is a sample size formula. It tells you how many people to survey from a known population — it does not extend your conclusions past that population, and calculating it correctly does not license a national claim. How the calculation itself works is set out in the guide to writing Chapter Three.
The sentence that protects you is short: “within the scope of the study” or “among the staff of the organisation studied”. Add it once to each conclusion and most of the overreach disappears.
Which words weaken a claim, and which strengthen it?
Sort them by strength, and choose deliberately rather than by ear.
| Strength | Verbs | Modals and adverbs | Frames |
|---|---|---|---|
| Weakest | appears to, seems to | may, might, possibly, tentatively | “one possible interpretation is…” |
| Cautious | suggests, indicates, points to | may well, arguably, largely | “the findings suggest that…” |
| Neutral | shows, reports, reveals, found | generally, typically | “the study found that…” |
| Confident | demonstrates, establishes | clearly, consistently | “the data establishes that…” |
| Strongest | proves, confirms | certainly, undoubtedly, always | “this proves that…” |
For most Nigerian undergraduate projects the honest band is the second and third rows. The bottom row is almost never available, and a panel that sees “proves” will spend its first question there.
Hedging is not padding. One hedge per claim is enough. “It may possibly appear to somewhat suggest” is four hedges on one verb and reads as an author who does not believe their own data.
Which sentences overclaim without looking like it?
Six constructions do almost all the damage, and none of them contains the word “prove”.
- “significantly influences” — “significant” is a statistical result about probability; “influences” is a causal claim. Joining them turns a p-value into a mechanism. Write “was significantly related to”.
- “the study shows that Nigerians…” — you surveyed one organisation. Name it.
- “all respondents agreed” — check the frequency table. Nearly always it was most, not all.
- “this confirms the theory” — one undergraduate survey does not confirm a theory. It is consistent with it.
- “there is a need for government to…” — a recommendation with no finding behind it. If no result points at government, government does not belong in your recommendations.
- “the findings revealed a high level of…” — “revealed” implies something hidden was uncovered. A questionnaire mean was measured, not revealed.
What if the null hypothesis was rejected but the effect is small?
Then you report both, in that order, and you say what the size means. Rejecting a null hypothesis says the relationship is unlikely to be zero. It says nothing about whether it is large enough to matter.
“The null hypothesis was rejected (r = .21, p = .03), indicating a statistically significant but weak positive relationship between the two variables. The strength of the relationship suggests that other factors not measured in this study account for most of the variation in the dependent variable.”
That second sentence is what separates a student who ran a test from one who understood it, and it is one of the strongest things you can say at a defence. The mechanics of presenting the decision itself sit in the guide to writing Chapter Four table by table.
How do I hedge without sounding unsure of my own work?
By hedging the scope rather than the finding. There is a large difference between these two sentences:
✗ “It may possibly be that training is somewhat related to productivity.”
✓ “Among the staff surveyed, training was significantly related to productivity, though the design does not establish the direction of the relationship.”
The second is more confident, not less. It states the finding flatly and then limits what may be concluded from it. That is the register a panel reads as competence: certain about what you measured, precise about what you did not.
Where in Chapter Five does hedging belong, and where is it wrong?
- Summary of findings — no hedging. These are your numbers. State them flatly in the past tense. A hedge here reads as doubt about your own arithmetic.
- Conclusions — hedge the scope. Present tense, bounded to the population studied.
- Discussion of the literature — hedge the agreement. “This is consistent with Okafor (2022)” rather than “this confirms Okafor (2022)”.
- Recommendations — do not hedge. A recommendation is an instruction. “It is recommended that management introduce…” not “management may possibly wish to consider”. A hedged recommendation is one nobody will act on.
- Contribution to knowledge — hedge hard. Nigerian departments examine this section closely, and an undergraduate contribution is normally an addition to evidence in a specific setting, not a new theory. The section is covered in the guide to writing Chapter Five.
What does a panel do with an unhedged finding?
They test it against your own methodology, and they do it with questions you can predict: What population did you generalise to? How did you establish causation with a survey? Which respondents are covered by the word “all”? Would this hold in a different state?
An unhedged sentence hands the panel the question. A properly scoped one closes it before it is asked, which is why this is the cheapest defence preparation available — the full inventory of what panels ask is in the guide to project defence questions in Nigeria.
What does the fix look like on a real paragraph?
Before:
The findings revealed that training significantly influences employee productivity. This proves that Nigerian organisations that train their staff will be more productive. All respondents agreed that training is important. It is therefore concluded that training is the major determinant of productivity in Nigeria.
After:
The study found a significant positive relationship between training and employee productivity among the staff surveyed (r = .48, p < .05). Because the design was correlational, it establishes that the two variables move together rather than that one produces the other. Most respondents (84 per cent) rated training as important. Within the scope of the study, training is significantly associated with productivity, and the strength of the relationship indicates that other factors not measured here also contribute.
The findings did not change. Four words did: revealed became found, influences became related to, proves disappeared, and all became 84 per cent.
Keep the claim and the number in the same document
Tesify holds your results and your conclusions in one connected project, so a conclusion that has outrun its data is something you can see rather than something a panel finds for you. Over 9,000 students have written more than 15,000 chapters with it, and every word is still written by you.
Frequently asked questions
How strongly can I state my findings in Chapter Five?
As strongly as your design allows. A descriptive survey supports statements about what your respondents reported; a correlational study supports statements that two variables move together. Neither supports a causal claim or a claim about a population you did not sample.
Can I say my study proves something?
Almost never. “Proves” belongs to replicated experimental evidence. An undergraduate survey reports, finds or shows. Using “proves” is the single most reliable way to attract the first question at your defence.
What is wrong with “significantly influences”?
It joins a statistical result to a causal claim. “Significant” describes probability; “influences” describes a mechanism your design did not test. Write “was significantly related to” instead.
Can I generalise my findings to all Nigerians?
No, unless you drew a national probability sample, which no undergraduate project does. Your findings apply to the population your sample was drawn from. Add “within the scope of the study” to each conclusion.
Does a large Taro Yamane sample let me generalise further?
No. Taro Yamane tells you how many people to survey from a known population. It does not extend your conclusions beyond that population, however large the sample or however correct the calculation.
My null hypothesis was rejected but the correlation is weak. What do I write?
Report both: the relationship is statistically significant and weak. Then say that the strength implies other unmeasured factors account for most of the variation. That sentence shows you understood the test rather than just ran it.
Will hedging make my project look weak?
The opposite, if you hedge the scope rather than the finding. State what you measured flatly, then limit what can be concluded from it. Panels read that as competence; they read an unbounded claim as inexperience.
How many hedges should one sentence have?
One. Stacking them — may possibly appear to somewhat suggest — reads as an author who does not believe their own data, and it is as damaging as overclaiming.
Should recommendations be hedged?
No. A recommendation is an instruction and should be written as one: “It is recommended that management introduce…” A recommendation buried under modals is one nobody will act on, and it still needs a finding behind it.
Can I say my findings confirm a theory?
Say they are consistent with it. One undergraduate study in one setting adds evidence; it does not confirm a theory, and a panel member who works on that theory will notice the difference.
Is “all respondents agreed” ever correct?
Only if your frequency table shows 100 per cent, which is rare. Check the table and write the actual percentage. A specific number is stronger than “all” and it cannot be contradicted by your own appendix.
Where does hedging not belong at all?
In the summary of findings. Those are your own measurements, stated in the past tense, and hedging them suggests you are unsure of your arithmetic rather than careful about your inference.