1. I. Introduction and Data Collection B. Sampling

2. Example
We are interested in taking a sample from the student body at the university of Kentucky.
Suppose we collect data from all students who are in attendance at UK’s first home basketball game. What is the problem with this sample?
How should we take a sample from this population in order for it to be representative of the population?
Why is a random sample representative of the population?

3. Suppose we have a list of all UK students separated by department
Suppose we have a list of all UK students separated by department. We decide to randomly select 10 departments and then randomly sample 50 people from each department. This would be classified as what type of sample?
Suppose that the purpose of selecting a random sample of UK students is to compare freshman, sophomores, juniors, and seniors. What type of sampling should be used in this case?

4. Suppose we had a list of all students at UK
Suppose we had a list of all students at UK. We used statistical software to randomly select 500 students. The software ensures that all samples of size 500 have an equal opportunity of being selected. This would be what type of sample?
Suppose that we have a list of all UK students in alphabetical order. We decide to start at a random point on the list and select every 50th person to be part of our sample. This is what type of sampling?

5. Example
Suppose that from a sample of 2000 parents, we find that 1250 say they would support their son playing youth football.
What is the sample proportion?
What is the margin of error?
Construct and interpret a 95% confidence interval for the population proportion.
What happens to margin of error as you increase the sample size?