Sampling and Experimental Design

voluntary response/self selected sample

respondents decide if they want to be included in the study

• these are biased, should not be used

• way in which we choose sample directly impacts results

representative sample

characteristics of sample closely match characteristics of population to be proportionally represented

• ex: population gender ratio is 40/60 and so is sample

• every possible sample size of n has the same chance of being chosen

sampling error

difference between sample result and population result

observational studies

researchers observe and measure individuals but do not modify them in any way

cross sectional study

data are measured at 1 time point

observational studies

researchers observe and measure individuals but do not modify them in any way

cross sectional study (type of observational)

data are measured at 1 time point

longitudinal (prospective) study (type of observational)

data are collected over multiple time points (can show trends overtime)

retrospective (case control study) (type of observational)

researchers go “back in time” and collect data from the past in order to learn more about the current status of a variable/topic

• Ex: What factors contribute to alcoholism?

experiments

researchers apply some treatment (modification) to study participants and observe effects

• ex: clinical trials

treatment groups

subjects receive special/innovative treatment

control group

subjects are not given special treatment, but rather are treated as usual/given a placebo

blinding, blocking, randomization

Confounding is controlled by these three things

confounding

effects of variables become intertwined so that individual effects of variables cannot be appropriately identified

blinding

participants don’t know whether they are receiving the treatment or placebo. can be single or double blind