Sample and population concepts in statistical studies MCQs With Answer
Understanding sample and population concepts is essential for B. Pharm students conducting research, clinical trials, or drug surveillance. This introduction explains key ideas—population, sample, sampling frame, sampling methods (simple random, stratified, cluster, systematic, convenience), sampling bias, sample size determination, parameters versus statistics, sampling error, and representativeness—within the context of pharmaceutical studies and biostatistics. Emphasis on estimation, confidence intervals, and the central limit theorem helps link theory to practice in drug development, pharmacovigilance, and epidemiological surveys. These concepts guide sound study design, valid inference, and reliable conclusions in pharmacy research. Now let’s test your knowledge with 30 MCQs on this topic.
Q1. What is the best definition of a population in a statistical study relevant to B.Pharm research?
- The entire set of individuals, experimental units, or observations about which we want to draw conclusions
- A small group selected to pilot the study before the main trial
- The list of all available research assistants
- The dataset obtained after data cleaning
Correct Answer: The entire set of individuals, experimental units, or observations about which we want to draw conclusions
Q2. In contrast, what is a sample?
- A parameter calculated from the whole population
- A subset of the population selected for measurement or observation
- The theoretical distribution of a statistic
- A way to randomize treatment allocation
Correct Answer: A subset of the population selected for measurement or observation
Q3. Which term refers to a numerical summary describing a population?
- Statistic
- Estimator
- Parameter
- Sample
Correct Answer: Parameter
Q4. Which term refers to a numerical summary calculated from a sample?
- Parameter
- Statistic
- Population
- Frame
Correct Answer: Statistic
Q5. What is a sampling frame in the context of a pharmacological survey?
- The statistical test used to analyze data
- The list or mechanism used to identify all elements of the population from which the sample is drawn
- The dataset after applying exclusion criteria
- The confidence interval around the sample mean
Correct Answer: The list or mechanism used to identify all elements of the population from which the sample is drawn
Q6. Which sampling method ensures each individual in the population has an equal probability of selection?
- Convenience sampling
- Stratified sampling
- Simple random sampling
- Purposive sampling
Correct Answer: Simple random sampling
Q7. When is stratified sampling most appropriate in B.Pharm studies?
- When population is homogeneous for the outcome of interest
- When you want to ensure representation from key subgroups like age, gender, or disease stage
- When quick non-random data collection is required
- When clusters (e.g., hospitals) are the main sampling units
Correct Answer: When you want to ensure representation from key subgroups like age, gender, or disease stage
Q8. What is cluster sampling advantage for multicenter drug studies?
- Always gives lower sampling error than stratified sampling
- Reduces travel costs by sampling whole groups such as hospitals or clinics
- Eliminates the need for randomization
- Guarantees no selection bias
Correct Answer: Reduces travel costs by sampling whole groups such as hospitals or clinics
Q9. Which is a non-probability sampling method commonly used for pilot studies?
- Systematic random sampling
- Convenience sampling
- Stratified random sampling
- Cluster random sampling
Correct Answer: Convenience sampling
Q10. What does sampling bias refer to?
- Random variation due to small sample size
- A systematic error causing the sample to differ from the population in a non-random way
- The distribution of a statistic across repeated samples
- The calculation used to determine sample variance
Correct Answer: A systematic error causing the sample to differ from the population in a non-random way
Q11. Which factor does NOT directly affect sample size calculations?
- Desired confidence level
- Acceptable margin of error
- Population variability (standard deviation)
- The font used in the survey questionnaire
Correct Answer: The font used in the survey questionnaire
Q12. How does increasing sample size affect the standard error of the mean?
- Standard error increases linearly with sample size
- Standard error decreases, approximately proportional to the square root of the sample size
- Standard error stays constant
- Standard error becomes equal to the population standard deviation
Correct Answer: Standard error decreases, approximately proportional to the square root of the sample size
Q13. For estimating a population proportion (e.g., adverse event rate), which inputs are needed for sample size?
- Expected proportion, confidence level, and margin of error
- Only population mean and variance
- Number of investigators and study duration
- Type of statistical software
Correct Answer: Expected proportion, confidence level, and margin of error
Q14. What is the finite population correction (FPC) used for?
- Adjusting standard errors when sample size is a large fraction of a small population
- Correcting measurement error in lab assays
- Changing the confidence level for hypothesis testing
- Estimating treatment effect in crossover trials
Correct Answer: Adjusting standard errors when sample size is a large fraction of a small population
Q15. Which statement about the central limit theorem (CLT) is true?
- CLT states sample means follow a t-distribution regardless of sample size
- CLT implies the distribution of sample means approaches normality as sample size increases, even if the population is non-normal
- CLT only applies to population proportions
- CLT is irrelevant for B.Pharm studies
Correct Answer: CLT implies the distribution of sample means approaches normality as sample size increases, even if the population is non-normal
Q16. What is non-sampling error in pharmaceutical surveys?
- Error arising solely from selecting a small sample
- All random fluctuations captured by standard error
- Errors due to data collection, measurement, nonresponse, or processing
- The difference between sample mean and population mean due to chance
Correct Answer: Errors due to data collection, measurement, nonresponse, or processing
Q17. Which approach reduces nonresponse bias in a follow-up pharmacovigilance study?
- Ignore missing data and analyze responders only
- Use strategies like reminders, multiple contact modes, and analyzing nonresponders characteristics
- Decrease sample size to include only committed participants
- Switch to convenience sampling
Correct Answer: Use strategies like reminders, multiple contact modes, and analyzing nonresponders characteristics
Q18. In systematic sampling, how is the sample selected?
- By randomly selecting clusters only
- By choosing every kth element from a list after a random start
- Only from volunteers who respond first
- By stratifying and then using simple random sampling within strata
Correct Answer: By choosing every kth element from a list after a random start
Q19. What is purposive (judgmental) sampling best used for?
- Estimating population prevalence with high precision
- Selecting specialized subjects who meet predefined criteria for in-depth qualitative studies
- Ensuring randomization in clinical trials
- Calculating confidence intervals for drug efficacy
Correct Answer: Selecting specialized subjects who meet predefined criteria for in-depth qualitative studies
Q20. Which sampling design is most appropriate for a nationwide prevalence survey of drug side effects requiring representation by region and urban/rural status?
- Simple random sampling without stratification
- Stratified multistage cluster sampling
- Convenience sampling at a single tertiary hospital
- Pilot sampling only
Correct Answer: Stratified multistage cluster sampling
Q21. Which describes sampling error?
- Systematic bias due to poor measurement instruments
- The variability between a sample statistic and the true population parameter due to random sampling
- Error introduced by using a wrong statistical test
- Nonresponse caused by loss to follow-up
Correct Answer: The variability between a sample statistic and the true population parameter due to random sampling
Q22. For comparing a continuous outcome between two treatment groups, increasing sample size primarily increases what?
- The p-value
- The study’s statistical power to detect a true effect
- The population variance
- The magnitude of the treatment effect
Correct Answer: The study’s statistical power to detect a true effect
Q23. When designing a case-control study in drug safety, how should controls be selected?
- From a completely different population to avoid confounding
- From the same source population that produced the cases and representative of exposure distribution if cases had not developed disease
- Only from healthy volunteers unrelated to cases
- By picking the first available patients in the clinic
Correct Answer: From the same source population that produced the cases and representative of exposure distribution if cases had not developed disease
Q24. Which is TRUE about multistage sampling?
- It always provides a simple random sample of individuals
- It samples in stages, such as selecting clusters first, then sampling individuals within selected clusters
- It is identical to stratified sampling
- It cannot be used in large-scale surveys
Correct Answer: It samples in stages, such as selecting clusters first, then sampling individuals within selected clusters
Q25. In randomized controlled trials, why is random sampling of participants less important than random allocation?
- Random allocation eliminates selection bias between treatment arms, while external validity depends on sampling
- Random sampling always reduces internal validity
- Random allocation is used only for open-label trials
- Because sampling has no effect on generalizability
Correct Answer: Random allocation eliminates selection bias between treatment arms, while external validity depends on sampling
Q26. Which measure indicates how well a sample represents its population?
- p-value
- Representativeness assessed by comparing known population characteristics and response rates
- Alpha error
- Number of study sites
Correct Answer: Representativeness assessed by comparing known population characteristics and response rates
Q27. If a B.Pharm study has high variability in outcome, what effect does this have on required sample size?
- Required sample size decreases
- Required sample size increases to maintain the same precision
- Required sample size is unaffected by variability
- Study must switch to non-probability sampling
Correct Answer: Required sample size increases to maintain the same precision
Q28. What is the main goal of pilot sampling in pharmaceutical research?
- To replace the main study
- To assess feasibility, refine procedures, estimate variability, and inform sample size calculations
- To intentionally bias results to test robustness
- To avoid ethical review processes
Correct Answer: To assess feasibility, refine procedures, estimate variability, and inform sample size calculations
Q29. Which situation most likely causes selection bias?
- Randomly selecting participants from the full registry
- Excluding participants who are too sick to attend follow-up visits without accounting for them analytically
- Using double-blinding during outcome assessment
- Calculating confidence intervals correctly
Correct Answer: Excluding participants who are too sick to attend follow-up visits without accounting for them analytically
Q30. In prevalence surveys, why might cluster sampling increase the design effect?
- Because measurements within clusters tend to be more similar, increasing variance compared to simple random sampling
- Because clusters always have equal outcomes
- Because cluster sampling eliminates intra-cluster correlation
- Because cluster sampling reduces the need for larger samples
Correct Answer: Because measurements within clusters tend to be more similar, increasing variance compared to simple random sampling
