parameter vs statistic
- parameter: a numerical measurement describing some characteristic of a population
- statistic: a numerical measurement describing some characteristic of a sample
2 types of quantitative data:
- discrete: when the number of possible values is either a finite number or a "countable" number (0,1,2,3,...)
- continous: infinitely many values that correspond to some continuous scale (2.243115 gallons of milk per day)
4 levels of measurement:
- nominal: qualitative; data consists of names only and cannot be arranged in an ordering scheme (yes, no, undecided)
- ordinal: qualitative; data that can be arranged in some order, but differences between values are meaningless (A, B, C, D, or F)
- interval: quantitative; data can be arranged in order and difference between values has meaning. however, no natural zero starting point
- ratio: quantitative; interval level except there is a natural zero starting point.
observational studies vs experimental
- observation: observing and measuring specific characteristics without attempting to modify the subject.
- experimental: apply some treatment and then observe its effect on the subjects.
types of sampling (5)
- simple random sample: a sample of n subjects is selected so that every sample has the same chance of being chosen
- systematic: select every kth element in the population
- convenience: use results that are easy to get
- stratified: subdivide the population into subgroups that share the same characteristics then draw a sample from each group. (male or female then 5% from each)
- cluster: divide population area into sections then randomly select some of those clusters and all of their members