Given below are two statements: one is labelled as Assertion A and the other is labelled as Reason R:

Assertion A: Too small a sample leads to biased conclusions.
Reason R: When the sample is too small, it may not cover all the attributes of the population to be studied.
In the light of the above statements, choose the correct answer from the options given below:

Correct option is A

· Assertion A: Too small a sample leads to biased conclusions is true. When the sample size is too small, it may not represent the larger population accurately. This leads to conclusions that are not generalizable and might be skewed, producing bias in the results.
· Reason R: Reason R is also true. When the sample size is small, it cannot possibly capture all the varied characteristics (attributes) of the population. This leads to a lack of representation, which makes the findings of the study less reliable and valid. A larger, more diverse sample is needed to ensure the findings are more comprehensive and applicable to the entire population.
· Relationship between A and R: Reason R correctly explains Assertion A. A small sample cannot cover the full diversity of the population, which directly contributes to biased conclusions. Therefore, Reason R is the correct explanation for why a small sample leads to biased results.
Information Booster
· Sample Size and Statistical Power: A small sample size reduces the statistical power of a study, making it harder to detect true relationships or effects. This can lead to inaccurate results and misinterpretations.
· Bias in Sampling: Small samples are more prone to sampling bias, meaning certain groups or characteristics of the population might be overrepresented or underrepresented, distorting the findings.