ITS-Ch07-Sampling and Sampling Distribution Quiz

What is simple random sampling?

• Selecting a sample from a population where only the most educated individuals are chosen

• A method of selecting a sample from a population based on their age

• Choosing a sample from a population based on their income level

• A method of selecting a sample from a population where each individual has an equal probability of being chosen.

What is the main advantage of simple random sampling?

• Limited representation of the population

• Higher cost and time-consuming

• Selection based on personal preference

• Equal chance of selection for every member of the population

What is stratified sampling?

• A sampling method that involves selecting only the most common characteristics of the population

• A sampling method that involves dividing the population into subgroups and then taking random samples from each subgroup.

• A sampling method that involves taking samples from only one specific subgroup of the population

• A sampling method that involves selecting samples based on convenience rather than randomness

When is stratified sampling most useful?

• When the population is completely homogeneous

• When the population is too large to handle

• When the population is not divided into subgroups

• When the population can be divided into distinct subgroups with similar characteristics.

What is systematic sampling?

• A sampling method where the sample is chosen based on the researcher's personal preference.

• A sampling method where only the first member of the population is selected for the sample.

• A sampling method where every member of the population is selected for the sample.

• A sampling method where every nth member of the population is selected to be included in the sample.

How is systematic sampling different from simple random sampling?

• Systematic sampling involves selecting every nth item from the population, while simple random sampling involves selecting items randomly without replacement.

• Systematic sampling involves selecting every item from the population, while simple random sampling involves selecting items randomly with replacement.

• Systematic sampling involves selecting items based on a specific pattern, while simple random sampling involves selecting items based on a complex algorithm.

• Systematic sampling involves selecting items randomly without replacement, while simple random sampling involves selecting every nth item from the population.

What is cluster sampling?

• A sampling technique where the population is divided into overlapping groups and a random sample of groups is selected for analysis.

• A sampling technique where the population is divided into non-overlapping groups and a non-random sample of groups is selected for analysis.

• A sampling technique where the population is divided into individual units and a random sample of units is selected for analysis.

• A sampling technique where the population is divided into clusters and a random sample of clusters is selected for analysis.

In what situations is cluster sampling often used?

• Small and concentrated populations

• Homogeneous groups

• Large and geographically dispersed populations

• Randomly selected individuals

What is convenience sampling?

• A non-probability sampling technique where subjects are selected based on their convenient accessibility and proximity to the researcher.

• A sampling technique that involves selecting every nth individual from the population

• A sampling technique that involves selecting individuals who are most similar to the researcher

• A sampling technique that involves selecting individuals based on their willingness to participate

What are the limitations of convenience sampling?

• Convenience sampling may not accurately represent the entire population as it relies on easily accessible subjects, leading to potential bias and lack of generalizability.

• Convenience sampling accurately represents the entire population

• Convenience sampling ensures generalizability

• Convenience sampling eliminates bias