Random Sampling Methods and Characteristics

To ensure every member of the population is included

To make sure the sample is as large as possible

To give each member of the population an equal chance of being selected

To select members based on their characteristics

Because it would be too expensive

Because we don't know the entire population's characteristics

Because it would require too many resources

Because it would be too time-consuming

Cluster random sample

Systematic random sample

Stratified random sample

Simple random sample

Based on their age

By choosing equal numbers from different groups

At total random, like drawing names from a hat

By selecting every tenth person

There is a specific order or system to the selection process

All participants are selected at once

Participants are selected based on their preferences

Participants are chosen from different groups

It uses a computer to randomly select participants

It selects participants based on their location

It divides the population into groups and selects randomly from each group

It selects participants based on their income

It ensures every member of the population has an equal chance of being selected

It is the most cost-effective method

It is the easiest method to implement

It requires the least amount of resources

Simple random sample

Cluster random sample

Systematic random sample

Stratified random sample

To ensure the sample is large enough

To avoid bias and ensure every member has an equal chance of selection

To make the process faster

To reduce the cost of sampling

Random sampling is only used in scientific research

Random sampling is the most expensive method

Random sampling ensures a representative sample and valid inferences

Random sampling is only necessary for large populations