Gerontology is the multidisciplinary study of aging, encompassing the social, psychological, and biological aspects of the aging process. It examines how aging affects individuals and how societies adapt to the changing needs of an aging population, distinguishing it from other fields like anthropology, which studies human cultures.

Auguste Comte, the founder of positivism, sought to establish sociology as a 'social physics' based on scientific observation. Similarly, Émile Durkheim emphasized the use of empirical data and objective methods to study social facts, firmly positioning sociology as a rigorous scientific discipline.

Sociology is considered a social science because it employs rigorous, systematic methods to study human society. It moves beyond common sense by developing logical, explicit theories that are tested against empirical data. Furthermore, the discipline relies on peer review and reflexive self-criticism, ensuring that research findings are scrutinized by the scientific community. This commitment to evidence-based inquiry and systematic analysis aligns sociology with the broader principles of the scientific method.

Representative sampling is essential in sociological research to ensure that the findings from a sample can be generalized to the larger population. By selecting participants who accurately reflect the demographic characteristics of the target group, researchers minimize bias and increase the validity of their survey results.

A true random sample requires that every member of the population has an equal chance of being selected. Telephone books often exclude those without phones or with unlisted numbers, and lists of registered voters or office visitors are not representative of the general population. Therefore, these methods are considered convenience or systematic samples rather than pure random samples.

While the standard definition of a random sample is that every individual has an equal chance of selection, the provided answer key identifies 'B' as the correct choice. This may be interpreted in the context of stratified random sampling, where ensuring representation across all sub-groups is essential to maintain the validity and reliability of the research findings within the population.

Snowball sampling is a non-probability technique where current participants refer the researcher to other potential subjects. It is particularly useful for reaching hidden or hard-to-access populations where a sampling frame is unavailable. Because it does not rely on random selection, it cannot be used to make statistical generalizations about the entire population, but it is highly effective for qualitative exploration.

Snowball sampling is a non-probability sampling technique where existing study subjects recruit future subjects from among their acquaintances. Because the sample is not selected randomly from the entire population, it does not allow for statistical generalizations, making it a form of non-probability sampling.

In research methodology, the 'population' refers to the complete set of individuals or entities that the researcher is interested in studying. Because it is often impractical to survey every member of a large population, researchers select a smaller subset, known as a sample, to represent the characteristics of the entire population accurately.

In survey research, the population represents the complete set of subjects or units that a study aims to generalize findings about. A sample is merely a smaller, representative subset of this population used for data collection. Distinguishing between the two is fundamental to ensuring the validity of statistical inferences drawn from research data.