unit 3 terms (sampling and bias)

Simple Random Sampling

Everyone has an equal chance

Chosen randomly

Systematic Random Sampling

Population is ordered in some way

There is a randoms starting point

And the sample is chosen at a regular interval

Stratified random samplinh

Population is divided into groups

An equal proportion of each group is chosen

Cluster random sampling

Population is divided into groups

Several groups are randomly selected and all members of those groups make up the sample

Multi stage random sampling

Population is organized into groups

Different group are chosen

From those groups a random sample is chosen

Uses several layers

Destructive sampling

Random sample but each sample is destroyed during the process

Voluntary sampling

Sample is by volunteer only

Convenience sampling

Sample of people who are easily accessible

Sampling Bias

Sample doesn't accurately represent a population

Non response bias

Results are influenced because some people don't respond

Can occur from volunteer surveys

Household bias

Respondent is overrepresented

Response bias

Poorly designed question

Questions that imply the answer

Measurement bias

Poor collection of data

If there are only 3 options, people will choose one of those instead of typing in the other option