# Describe to susan how to take a sample of the student population that would not represent the population well.

Question: Describe to susan how to take a sample of the student population that would not represent the population well.

Susan! Let's explore two scenarios related to sampling from a student population:

1. Poor Representation Sample:

- Imagine you decide to take a sample of students, but you unintentionally end up with a group that doesn't accurately represent the entire student population.

- Example: Suppose you randomly select only female students or only male students for your sample. This would be biased because it excludes the other gender. For instance, if you choose female students, you might miss out on valuable insights from male students, and vice versa¹.

- This type of sampling is called stratified sampling, where you organize the sample based on shared characteristics (in this case, gender).

2. Well-Represented Sample:

- Now let's consider a scenario where your sample represents the entire student population effectively.

- Example: You randomly select students from each grade level. For instance, you pick 5-10 students from every classroom or let the principal randomly choose two classrooms from each grade. This approach ensures that every grade level is represented, and each student has an equal chance of being selected.

- This type of sampling is known as a cluster population sample.

Remember, Susan, a sample is a smaller subset of the population from which you collect data. It's essential to choose a sample method that accurately reflects the characteristics of the entire population.

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