Which of the following best describes a random sample?

Which of the following best describes a random sample?

• A. A sample where every member of the population had an equal chance of being selected
• B. A sample that is too small to support a generalization
• C. A sample that adequately reflects the various groups in a population
• D. A sample that represents expert opinions in a field

Answer: (A)

A random sample is characterized by the principle that every member of the population has an equal chance of being selected. This ensures that the sample is truly representative of the population as a whole, allowing for more reliable conclusions to be drawn from the data. The randomness helps to eliminate bias in the selection process, which can skew results and lead to inaccurate generalizations. In contrast, the other options focus on different aspects of sampling. For example, a small sample size, while it may lead to unreliable results, does not inherently capture the concept of randomness. Similarly, stratified or purposive samples might reflect various groups or expert opinions, but these samples are not random. Random sampling is a foundational method in statistics that maximizes the likelihood of obtaining a representative snapshot of the population, which is critical for valid analysis and conclusions.

A random sample is characterized by the principle that every member of the population has an equal chance of being selected. This ensures that the sample is truly representative of the population as a whole, allowing for more reliable conclusions to be drawn from the data. The randomness helps to eliminate bias in the selection process, which can skew results and lead to inaccurate generalizations.

In contrast, the other options focus on different aspects of sampling. For example, a small sample size, while it may lead to unreliable results, does not inherently capture the concept of randomness. Similarly, stratified or purposive samples might reflect various groups or expert opinions, but these samples are not random. Random sampling is a foundational method in statistics that maximizes the likelihood of obtaining a representative snapshot of the population, which is critical for valid analysis and conclusions.