📘 Section 1: Explanations
1. Mean is the average of a set of values.
✅ Correct: C. Mean — It represents the central value of the readings.
❌ A. Variance → Measures spread, not central tendency.
❌ B. SD → Measures how values deviate from the mean.
❌ D. Range → Difference between highest and lowest.
2. Normal distribution rule (empirical rule):
✅ A. 68% — Values fall within ±1 SD in a normal curve.
❌ B. 75% → No basis in normal distribution.
❌ C. 50% → That’s just the median.
❌ D. 95% → This is for ±2 SDs, not ±1 SD.
3. Randomization ensures fairness in assigning treatments.
✅ C. Reduce bias — Prevents selection bias.
❌ A. Increase sample size → Unrelated to randomization.
❌ B. Improve power → Sample size & variability affect power more.
❌ D. Simplify analysis → May actually complicate it.
4. Glucose is a continuous variable.
✅ C. Continuous data — It has infinite measurable values.
❌ A/B/D → These are used for categories, not measurements.
5. Blood group has no order or ranking.
✅ C. Nominal — Pure labels (A, B, AB, O).
❌ A. Ordinal → Implies rank (e.g., pain scales).
❌ B/D → Interval and Ratio imply measurable scales.
6. Computing the mean is descriptive statistics.
✅ B. Computing the mean of a dataset — This summarizes data.
❌ A/C/D → These involve inferential or complex statistical modeling.
7. Comparative studies test ideas or theories.
✅ A. To provide hypotheses — Observations generate questions.
❌ B. Generate knowledge → Needs hypothesis tested first.
❌ C. Write papers → Not a scientific purpose.
❌ D. Collect data → Too vague.
8. Good research is never arbitrary.
✅ C. Arbitrary — It is not systematic, so it’s NOT a trait of science.
❌ A/B/D → All are true features of proper research.
9. A hypothesis is a reasoned assumption.
✅ B. Educated guess — Based on some prior knowledge.
❌ A. Proven fact → It's not yet tested.
❌ C/D → Not definitions of hypotheses.
10. Applying knowledge to solve real problems.
✅ B. Applied research — Seeks to improve patient outcomes.
❌ A. Basic → Is theoretical.
❌ C. Exploratory → Doesn’t aim at immediate solutions.
❌ D. Descriptive → Only observes, doesn’t intervene.
11. You must first define what you're solving.
✅ B. Identify the problem — Research starts with a clear question.
❌ A/C/D → These follow after problem identification.
12. Random sampling gives everyone equal chance.
✅ B. Random sampling — Minimizes selection bias.
❌ A. Stratified → Divides by subgroup.
❌ C. Systematic → Uses intervals (every 5th, etc.).
❌ D. Convenience → Based on ease, not randomness.
13. Primary data is first-hand (not from books).
✅ B. Interviews — Directly collected from people.
❌ A/C/D → Secondary data sources.
14. Data analysis converts numbers into meaning.
✅ B. To interpret and derive conclusions — Key goal of analysis.
❌ A. Simplify → Partial reason, not the main.
❌ C/D → These are different steps.
15. Reproducibility indicates reliability.
✅ B. Reliable — Repeating results confirms this.
❌ A. Valid → Refers to accuracy.
❌ C. Ethical → Irrelevant to repeatability.
❌ D. Practical → Not a measurement term.
16. Participants must know and agree.
✅ B. Informed consent — Protects autonomy.
❌ A/D → These are ethical violations.
❌ C → Irrelevant here.
17. Epidemiology focuses on exposure-disease link.
✅ C. Strength of association between exposure and disease — Measured via RR or OR.
❌ A/B → These are probabilities, not strength.
❌ D → Refers to absolute differences, not strength.
18. ANOVA needs some assumptions.
✅ D. Equal sample sizes in each group — Not a strict assumption.
❌ A/B/C → Required for valid ANOVA results.
19. Confidentiality protects patients.
✅ B. To ensure data security for participants — Especially critical in HIV studies.
❌ A → It’s about participants, not the researcher.
❌ C/D → Not related to confidentiality.
20. Representativeness means accurate reflection.
✅ B. A sample that reflects the population accurately — Ensures generalizability.
❌ A → Random is good but not enough.
❌ C → Equal groups are not required.
❌ D → Size alone doesn’t define representativeness.
