Question

how can you select a sample so that the information gained represents the entire population? select (select) of the population and ask each participant (select).

Explanation:

To select a sample that represents the entire population, we use random sampling (or probability sampling methods like simple random sampling, stratified sampling, cluster sampling, systematic sampling). Here's why:

• Random Sampling: Each member of the population has an equal chance of being selected. This minimizes bias and ensures the sample is representative. For example, in simple random sampling, you might assign numbers to all population members and use a random number generator to pick the sample.
• Other methods (stratified, cluster, systematic) also aim to reflect population characteristics by either dividing the population into groups (strata, clusters) or using a fixed interval (systematic) to select participants.

To fill in the blanks (based on typical survey/sampling terminology):

1. First blank: A random sample (or specific method like "simple random sample", "stratified sample")
2. Second blank: A representative portion (or "random subset", "proportionate group")

If the question is asking for the sampling method to ensure representativeness, the key is using a probability sampling method (e.g., random sampling) to select a sample where each member of the population has a known, non - zero chance of being included.

Answer:

To select a sample that represents the entire population, you can use a random sample (e.g., simple random sampling, stratified sampling, cluster sampling, or systematic sampling) of the population and ask each participant. In simple random sampling, for example, you assign a unique identifier to each member of the population and then use a random process (like a random number generator) to select the sample. This ensures that each member of the population has an equal chance of being selected, reducing bias and making the sample representative of the entire population.