Math flashcards

Simple random sample

Everyone in a population has an equal chance of being selected due to random chance

Stratified sampling

Population is divided into subsets of the population and then randomly sampled

Cluster sample

Population is divided into clusters → then the clusters are randomly selected and data is taken from them

Systematic sampling

Choosing the first item of a population and then every nth of a population

Census

Obtaining information from every individual in a population of interest

Convenience sampling

Participants are selected based on variability this causes bias

Voluntary response

Participants choose to participate in a sample group

Factor

A variable, the one that is being manipulated

Levels

The values is an experimenter chooses for the factor

Treatments

The different levels of a single factor

Response variable

The variable measured at the end of experiment

Control Group

Placebo group- The one not receiving treatment

Types of selection, bias

Under coverage: Members of the population are inadequately represented, nonresponse: Bias when responders differ in meaningful ways from nonresponders, voluntary response bias: Sample members are self selected, which causes bias

Response bias

Leading question/wording: The wording of the question favors one responds over another, Social desirability: Response may be biased towards what they believe is Socially desirable

Biased sampling

Voluntary and connivence

Unbiased sampling

Simple random sampling, stratified sampling, cluster sampling, systematic sampling

Selection bias

Occurs when the sample selected is not representative of the population

Response bias

Respondents answers are influenced by other factors

Sampling bias

Sample is not representative of target population