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📝 Statistical analysis in biology (7 MCQs)

📖 From Campbell Biology • 1. Evolution and the theme of Biology and Scientific Inquiry • 7 questions available

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What is Statistical analysis in biology?

Definition:
Statistical analysis in biology is the application of mathematical and computational methods to analyze biological data, summarizing and interpreting patterns, testing hypotheses, and determining the probability that observed results are due to chance, and it is essential for making objective decisions about the significance of experimental outcomes, ensuring rigor and reproducibility in research.

Working:
Statistical analysis works by using tests such as t-tests (comparing two group means), ANOVA (comparing multiple groups), chi-square (analyzing categorical data), and regression (examining relationships), and the results are interpreted using p-values, where $p < 0.05$ indicates that the results are statistically significant (unlikely due to chance), and confidence intervals provide a range of plausible values for the true effect, enabling researchers to draw conclusions with quantified uncertainty.

Example:
A simple example is comparing the growth of plants under two light conditions, where a t-test is used to compare the mean heights; if the p-value is 0.02, this indicates a statistically significant difference, suggesting that light condition affects growth, and the data can be used to support or reject the hypothesis.

Reason:
Statistical analysis is vital in biology because it provides a quantitative framework for decision-making, distinguishes real effects from random variation, and allows scientists to communicate the reliability of their findings, and it is indispensable in fields from genetics to ecology and medicine.

Easy

Medium

Hard

📝 All Statistical analysis in biology MCQs

Q1. A researcher records the number of seedlings produced by four treatments as 8, 9, 10, 11, and 42. Which statistic would best represent the typical production if the goal is to avoid distortion from the unusually large value?

A.Mean

B.Median ✅

C.Range

D.Maximum

💡 Difficulty: easy | ✅ Correct: B

📖 Explanation: The median is more resistant to extreme observations than the mean. Here, the value 42 pulls the mean upward substantially, whereas the median remains near the center of most observations and therefore better represents typical production.

Q2. Two groups of organisms have the same mean growth rate of 55 cm per week. Group A has values tightly clustered around 55, while Group B ranges from 11 to 99. What is the strongest conclusion?

A.The groups have identical variability because their means are equal

B.Group A has greater variability because its values are closer to the mean

C.Group B has greater variability even though both groups have the same mean ✅

D.The mean proves Group A grows faster

💡 Difficulty: medium | ✅ Correct: C

📖 Explanation: A mean describes central tendency but does not describe how widely observations are dispersed. Because Group B spans a much broader range, its measurements show greater variability despite having exactly the same mean as Group A.

Q3. A biologist measures enzyme activity before and after treatment in the same six samples. The mean activity increases from 40 to 52 units. Which additional analysis would most directly help determine whether the treatment consistently increased activity across samples?

A.Compare the maximum values only

B.Examine the paired changes for each sample ✅

C.Discard all values below the mean

D.Use only the post-treatment mean

💡 Difficulty: medium | ✅ Correct: B

📖 Explanation: Because the same samples were measured twice, each sample provides a natural before-and-after comparison. Examining individual paired changes reveals whether the observed average increase is consistent or driven by only one or two samples.

Q4. A student calculates the average mass of ten organisms and accidentally includes one measurement recorded as $500$ g instead of $50.0$ g. The resulting mean is much higher than expected. What is the best response?

A.Accept the mean because larger values always improve accuracy

B.Replace the value with the median automatically

C.Check the original measurement and correct it if the recording error is confirmed ✅

D.Remove every measurement above the mean

💡 Difficulty: hard | ✅ Correct: C

📖 Explanation: A suspicious value should first be checked against the original observation or measurement record. If $500$ g was a recording error for $50.0$ g, correcting the data is justified; deleting observations merely because they are large is not.

Q5. A graph shows the distribution of leaf lengths for two populations. Population X has most observations between 8 and 12 cm, while Population Y has observations spread fairly evenly from 4 to 16 cm. Which interpretation is most appropriate?

A.Population X has greater variability

B.Population Y has greater variability ✅

C.Both populations must have identical standard deviations

D.Population X necessarily has a larger mean

💡 Difficulty: medium | ✅ Correct: B

📖 Explanation: The wider spread of observations in Population Y indicates greater variability. A graph can reveal dispersion even when exact numerical statistics are unavailable, while the displayed distributions alone do not justify claiming that one mean is larger.

Q6. A researcher compares two habitats using 20 measurements from each. Habitat A has a mean of 12 and Habitat B has a mean of 15, but several extreme values occur in Habitat B. Which approach would provide the most informative comparison?

A.Compare only the two means

B.Ignore the extreme values without investigation

C.Compare measures of center together with measures of spread and inspect the underlying data ✅

D.Use the largest value from each habitat

💡 Difficulty: hard | ✅ Correct: C

📖 Explanation: Comparing means alone can hide important differences in variability and the influence of extreme observations. Examining the raw data and combining measures of center and spread provides a more reliable interpretation of the two habitats.

Q7. A dataset contains $n$ observations with mean 20. One observation equal to 20 is replaced by 35, while all other observations remain unchanged. Without calculating every value again, what must happen to the new mean?

A.It remains 20

B.It decreases below 20

C.It increases above 20 ✅

D.It becomes exactly 35

💡 Difficulty: easy | ✅ Correct: C

📖 Explanation: Replacing an observation equal to the original mean with a larger value increases the total sum while leaving the number of observations unchanged. Therefore, the new mean must increase above 20, although it will generally remain below 35.

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