Question

The method of selecting the sample in a sample survey affects how well the sample represents the population. Biased sampling methods, such as convenience sampling and voluntary response samples, produce data that can be misleading, resulting in incorrect conclusions. Simple random sampling avoids bias and produces data that give us confidence that the first step in our argument is sound.

Answer 1

The subject is on the importance of sampling methods in statistics and how they affect the study's validity. Simple random sampling and other random methods aim to avoid bias and ensure representativeness, sampling, which can lead to sampling bias.

Step-by-step explanation:

The question pertains to statistics and the importance of sampling methods in research studies. It emphasizes that the method of selecting a sample from a population significantly influences the accuracy and reliability Consequently, it is crucial to understand different sampling techniques and their potential biases.

Simple random sampling is a technique that gives each member of the population an equal chance of being included in the sample, thereby averting selection bias. Other random sampling methods include stratified sampling, cluster sampling, and systematic sampling.

These methods aim to create samples that are representative of the whole population. On the other hand, nonrandom sampling methods, such as convenience sampling and voluntary response samples, may result in biased data because they do not give all members of the population an equal opportunity to be selected.

Such nonrandom methods often lead to samples that may not accurately reflect the population's characteristics. This lack of representativeness can introduce sampling bias, ultimately leading to invalid conclusions about the population.