College Stats Vocab Quiz 2
Observational Study - observe & measure characteristics of interest of part of a population
Experiment - treatment is applied to a part of a population, called a treatment group, and responses are observed
Experimental Units - control group (given placebo) & treatment group (given treatment)
Confounding Variables - an experiment cannot tell the difference between the effects of different factors on a variable; ex: remodel coffee shop + new mall built next door = more$
Placebo Effect - subject reacts favorably to a placebo when in fact the subject has been given a fake treatment
Blinding - subjects don’t know if they have real treatment or placebo; used to minimize placebo effect
Double-Blind - neither subjects nor experimenters know who has placebo and who has real treatment
Randomization - process of randomly assigning subjects to different treatment groups
Completely Randomized Design - subjects are assigned to different treatment groups through random selection
Randomized Block Design - divide subjects with similar characteristics into blocks, and then within each block, randomly assign subjects to treatment groups
Matched Pairs Design - paired according to a similarity; one has treatment and other has placebo
Sample Size - # of subjects in sample; very important for testing & validity
Replication - repetition of experiment
Census - count or measure of whole population; very difficult and usually unpractical
Sampling - count or measure of part of a population; more common & feasible
Random Sample - every member of a population has an equal chance of being selected
Simple Random Sampling - every possible sample of the same size has the same chance of being selected
Stratified Sampling - divide population into groups(strata) and select random samples from each group; ex: FCHS into FR, SM, JR, SR and select 25 from each
Cluster Sampling - divide population into groups(cluster) and select all members in one or more, but not all, of the clusters; ex: IL into counties and select everybody from St. Clair & Cook but nobody from Monroe or Clinton
Systematic Sampling - choose every Kth of a population; ex: every 5th student that walks in every morning
Convenience Sampling - choose only members of population that are easy to get; often leads to biased studies; ex: surveying the kids in your stats kids when the population is the whole school