Sampling methods

Simple Random Sample (SRS)

equally likely to be chosen (x bias) —→ most ideal

stratified random sampling

population is divided into groups with similar characteristics —> accurately shows population (ex: think of an apartment with 4 floors of 9,10,11,12 graders = all different, pick one from each)

stratified —> layers

cluster sample

the population is divided into clusters and entire clusters are sampled (ex: a rectangular apartment with 5 different 동’s 101동,102,105,103,104 —> the population in 103 동 is chosen and is the sample group for everyone in that dong ** also the population in 103 cannot be completely poor or rich it has to represent the population accurately

systematic random sampling

specific rule is used to select members of a sample (needs to be a specific pattern) —> rule based ex: count every 10 ppl - 10 - 10- 10 -10

experiment

takes action to different groups (apply something and not apply something to get a result and compare)

sample survey

ask a question and record the answer + draw a conclusion from that

observational study

there is no treatment assigned to the subject being studied —> just observe and watch

biased sample

does not represent the population

asking questions in the wrong way can also lead to bias

question —> by phrasing the question in favor of the person asking, or advantageous to them it evokes a biased answer from the person receiving the question

convenience sample

only choosing subjects that are close in proximity

self-selected sample

using a sample made up of volunteers (only those who care enough to participate)

experimental group

group that receives the treatment used to compare effect of treatment to the effect of no treatment (control)

control group

the group that doesn’t receive the treatment (just used for comparison)