Using a Sample to Draw an Inference about a Population
What does it mean to say that we are going to use a sample to draw an inference about a population? | |
|Why is a random sample so important for this process? If we wanted a random sample of students in a cafeteria, why couldn’t we |
|just take the students who order Diet Pepsi with their lunch? |
|Comment on the statement, “A random sample is like a miniature population, wheras samples that are not random are likely to be |
|biased.” |
|Why would the students who order Diet Pepsi with lunch not be a random sample of students in the cafeteria? |
A population may be a large collection of people, objects, or measurements that we are interested in analyzing. However, it may not be practical to draw our inference using the entire population. In the case that it is not practical to draw a conclusion using the entire population, we will use a sample. For example, if I was conducting an analysis of the marital status of all women in the United States, it may be impractical to contact every single woman living in the Unites States. I would then contact a sample of women in the United States; I may contact 5,000 women and these 5,000 women would serve as my sample of all woman. I would then draw an inference about the marital status of women in the United States based on the sample. A random sample is very important for the process of sampling. A random sample is important because this type of sample will be representative of the entire population. Randomly choosing the sample from a population will allow for accurate results of the conclusion. If we wanted a random sample of students in a cafeteria we could not just take the students who order Diet Pepsi with their lunch because this sample would not be a random sample of a population. If we were to
|Why is a random sample so important for this process? If we wanted a random sample of students in a cafeteria, why couldn’t we |
|just take the students who order Diet Pepsi with their lunch? |
|Comment on the statement, “A random sample is like a miniature population, wheras samples that are not random are likely to be |
|biased.” |
|Why would the students who order Diet Pepsi with lunch not be a random sample of students in the cafeteria? |
A population may be a large collection of people, objects, or measurements that we are interested in analyzing. However, it may not be practical to draw our inference using the entire population. In the case that it is not practical to draw a conclusion using the entire population, we will use a sample. For example, if I was conducting an analysis of the marital status of all women in the United States, it may be impractical to contact every single woman living in the Unites States. I would then contact a sample of women in the United States; I may contact 5,000 women and these 5,000 women would serve as my sample of all woman. I would then draw an inference about the marital status of women in the United States based on the sample. A random sample is very important for the process of sampling. A random sample is important because this type of sample will be representative of the entire population. Randomly choosing the sample from a population will allow for accurate results of the conclusion. If we wanted a random sample of students in a cafeteria we could not just take the students who order Diet Pepsi with their lunch because this sample would not be a random sample of a population. If we were to