Assertion (A) : Findings of a research based on a large sample size of a population being studied can always be generalized to the whole population.
Reason (R) : Sample size does not ensure representativeness.
Analyzing Research Generalization and Sample Size
This question examines the relationship between sample size, representativeness, and the generalizability of research findings.
Assertion (A) Analysis
- Statement: Findings from a large sample size can always be generalized to the whole population.
- Evaluation: This statement is incorrect. While a large sample size increases the probability that the sample accurately reflects the population, it does not guarantee it. Generalizability also heavily depends on how the sample was selected (e.g., random sampling methods) and whether it is truly representative of the target population. Factors like sampling bias can significantly limit generalizability, regardless of sample size. The word "always" makes the assertion too absolute.
Reason (R) Analysis
- Statement: Sample size does not ensure representativeness.
- Evaluation: This statement is correct. A sample might be very large but still not representative if the selection method is flawed or biased. For instance, a large convenience sample might over-represent certain groups. True representativeness depends on the sampling technique used, ensuring all members of the population have a known chance of being included.
Conclusion
Since Assertion (A) is incorrect and Reason (R) is correct, the appropriate option is that (A) is incorrect, but (R) is correct.
Important Questions from Sample - Teaching
- Which of these statements does NOT describe snowball sampling correctly?
A. It is a non-probability sampling technique.
B. It is used when the target population is readily available.
C. Initial participants refer others to take part in the study.
D. It ensures equal chance of selection for all individuals.
E. It is commonly used in sociological and qualitative research.
Choose the correct answer from the options given below: - Assertion (A): The larger the sample size, the greater will be the power of the test.
Reason (R) : A large sample size results in smaller standard error of mean.
Codes : - In a Random Sampling distribution of means :
I. The standard error will decrease as the sample size increases.
II. The standard error will increase as the sample size increases.
III. The mean equals the population mean.
IV. The mean is not equal to the population mean. In a study, participants are recruited from local schools in urban area. The study is conducted on saturday so only the saturday working school take part. What type of sample is this ?
Multistage cluster sampling is helpful when :
