# Sample, Universe, Population

# Sample, Universe, Population

## Sample

A sub-section of the population
a **representation** of the population
**inference** is **generalized**

# Process of Sampling

- Define the population
- Develop Sampling Frame
- Select a Samling Method
- Determine sample size
- Execute the sampling process

**Sampling Population**
**Sample**

# Sampling Techniques

- Fixed vs sequential
- Probability vs non-probability
- Attributes vs

### Probability Sampling vs Non-probability Sampling

Probability | Non-probability |
---|---|

Every element has a chance of being in the sample | not equal chance |

sample is random | sample is chosen by researcher according to their convenience |

representative of the population | not representative |

graph TB A(Sampling Methods) A-->B(Probability) A-->C(Non Probability) B-->Z(Simple Random

Simple Stratified

Cluster

Systematic) C-->X(Purposive

Snowball

Convenience)

### Simple random

### Stratified random sampling

builds up from simple random
**divides** the population into groups depending on characteristic. groups = stratas
and then random sampling is performed
(Each subject only one strata; different stratas can have different number of subjects)

### Cluster Random Sample

A cluster is obtained by first dividing the population into randomly chosen sub-groups **(clusters)**
a random **assortment of clusters** = **the sample**
in stratified - there is no common characteristic needed

### Systematic Sampling

Every k ^{th} element
This method simply involves selecting participantsย **at a set interval**, starting from aย **random point**.