Theory component

ETC1000

Convenience Sampling - Definitions

,Selecting individuals who are easiest to access

Convenience Sampling

Sample is drawn from a group that is conveniently available

Convenience Sampling - Pros

Quick easy and inexpensive

Convenience Sampling - Cons

High risk of bias not representative

Simple Random Sampling - Definition,

Every individual in the population has an equal chance of being selected

Simple Random Sampling - How It Works

,Use random methods (e.g. random number generator) to select participants

Simple Random Sampling - Pros,

Minimizes selection bias easy to analyze

Simple Random Sampling - Cons,s

Can be impractical for large or dispersed population

Systematic Sampling - Definition,

Selecting every kth individual from a list

Systematic Sampling - How It Works,

Choose a random starting point then select every kth member

Systematic Sampling - Pros,

Simple to implement evenly spread

Systematic Sampling - Cons

,May introduce bias if there's a hidden pattern in the population

Cluster Sampling - Definition

Dividing population into clusters randomly selecting clusters then sampling all or some within them

Cluster Sampling - How It Works,

Randomly select entire groups (clusters) often based on geography

Cluster Sampling - Pros,

Cost-effective useful for large populations

Cluster Sampling - Cons,

Higher sampling error if clusters are not homogeneous

Stratified Sampling - Definition

,Dividing population into subgroups (strata) and sampling from each

Stratified Sampling - How It Works,

Population is divided into strata (e.g. age gender) and random samples taken from each

Stratified Sampling - Pros,

Ensures representation of key subgroups

Stratified Sampling - Cons

,Requires knowledge of population structure and strata

Sampling bias

Some members of the target population are less likely to be included than others

Attrition bias

,Participants who drop out of a study are different from the ones who remain

Volunteer bias,

Participants who choose to participate in studies are generally different to those who do not

Survivorship bias

,Successful observations are more likely to be represented than unsuccessful ones

Non-response bias,

Participants who refuse to participate or drop out of a study may be different to those who take part

Undercoverage bias

,Participants who are inadequately represented