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Interpreting Statistics & Drawing Valid Conclusions

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Edexcel IAL Biology • Unit 6: Practical Skills in Biology II

Interpreting Statistics & Drawing Valid Conclusions

🧾 Big idea: The test gives you a number. Turning it into a sentence an examiner can award marks for is a separate skill — and it is the one most often lost. Choose the right test, phrase the decision in terms of the null hypothesis, and claim exactly as much as the data allows and no more.

Summary — What This Topic Covers

Choosing between the three tests from the shape of the data
What p < 0.05 actually means
Phrasing a conclusion around the null hypothesis
The four claims a statistical test can never support
Writing a full conclusion, with the evidence quoted

1. Choosing the Right Test

WHAT ARE YOU ASKING? TEST ───────────────────────────────────────────────────────────────── Do these two groups have different means? t-test continuous data, roughly normal, two groups, n ≈ 10+ each Do these counts match what I predicted? chi-squared raw frequencies in categories, expected values from a hypothesis, no expected value below 5 Do these two variables change together? Spearman's rank pairs of measurements, at least 7 pairs, no normality assumed

The commonest error

Using a t-test on counts. If the data is "how many of each", it is chi-squared — no matter how tempting the two totals look like two means.

2. What p < 0.05 Means

The definition

p is the probability that a difference or correlation at least as large as the one observed would arise by chance if the null hypothesis were true.

p < 0.05 means that probability is less than 5 %, which biologists agree is low enough to call the result significant.

p < 0.05 significant less than 1 chance in 20 of arising by chance p < 0.01 highly significant p > 0.05 not significant the result could reasonably be chance

What p is not

p is not the probability that your hypothesis is correct, and it is not a measure of how big the effect is. It is only about how surprising the data would be if nothing were going on.

3. Phrasing the Decision

t-test and Spearman calculated ≥ critical → REJECT H₀ Chi-squared calculated ≥ critical → REJECT H₀ in every case: bigger than critical means significant REJECT H₀ → "there is a significant difference / correlation" ACCEPT H₀ → "no significant difference / correlation was found" NOT "there is no difference"

Why the wording matters

Accepting H₀ means you failed to find evidence of a difference — which may be because there is none, or because your sample was too small. The two are indistinguishable from the test alone, so the conclusion must not claim more than that.

4. Four Claims a Test Cannot Support

"This proves…" — statistics deal in probability, never proof. Write "suggests", "indicates" or "provides evidence that"
"X causes Y" from a correlation — only a controlled experiment establishes cause
"There is no difference" from a non-significant result — you found no evidence of one, which is a different statement
"The effect is large / important" from significance alone — with a big enough n, a trivial difference becomes significant

What mark schemes look for

5. A Full Conclusion

Practice Questions

Practice Question 1

Practice Question 2

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