Sampling Methods Quiz

What is simple random sampling?

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

• Selecting a sample by only including individuals who volunteer to participate

• A method of selecting a sample based on the alphabetical order of the population

• Choosing a sample by picking the first few individuals encountered

How is simple random sampling different from other sampling methods?

• Individuals are chosen based on their characteristics

• Only a specific group of individuals is chosen

• Each individual has an equal chance of being chosen

• The sample size is predetermined

Give an example of simple random sampling in real life.

• Drawing names out of a hat for a survey

• Selecting only people with blue eyes for a survey

• Picking the tallest person in a room for a survey

• Choosing the first 10 people who enter a store for a survey

What is stratified sampling?

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

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

• A sampling method in which the population is divided into subgroups and random samples are then taken from each stratum.

• A sampling method that involves selecting individuals who are conveniently available

How is stratified sampling useful in research?

• It is only useful for small sample sizes.

• It does not take into account the diversity of the population.

• It ensures that different subgroups within a population are represented in the sample.

• It only includes the most common characteristics of the population.

Provide an example of when stratified sampling would be appropriate.

• When studying the income levels of a city's population, stratified sampling would be appropriate to ensure people who earn different incomes are represented

• When analyzing the number of cars in a parking lot

• When researching the favorite color of people in a city

• When studying the height of trees in a forest

Explain systematic sampling.

• Selecting every member from the population

• Every nth member of the population is selected to be included in the sample.

• Including only the first few members of the population

• Choosing random members from the population

What are the advantages of systematic sampling?

• Provides inaccurate representation

• Efficient and structured approach, reduces bias, provides representative sample

• Increases bias in the sample

• Randomly selects samples

When is systematic sampling most effective?

• When the population is small and unevenly distributed.

• When the population is small and evenly distributed.

• When the population is large and evenly distributed.

• When the population is large and unevenly distributed.

Define random sampling and its importance in research.

• Random sampling is the method of selecting a sample from a larger population where the researcher intentionally chooses individuals who are not representative of the population.

• Random sampling is the method of selecting a sample from a larger population where each member of the population has an equal chance of being selected. It is important in research because it helps to ensure that the sample is representative of the population, which allows for generalization of the findings to the larger population.

• Random sampling is the method of selecting a sample from a larger population where the researcher picks the individuals they think are most relevant.

• Random sampling is the method of selecting a sample from a larger population where only the most common members are chosen.