# 3.3 - Sampling Methods

3.3 - Sampling Methods

As Jaylen has discovered, there are many different ways to select a sample from a population. Some of these methods are probability-based, such as the simple random, stratified, and cluster sampling methods that you'll read about below and in your textbook. Other sampling methods are not probability-based, such as convenience sampling methods which you'll read about below.

## Simple Random Sampling

To prevent sampling bias and obtain a representative sample, a sample should be selected using a probability-based sampling design which gives each individual a known chance of being selected. The most common probability-based sampling method is the simple random sampling method.

Using this method, a sample is selected without replacement. This means that once an individual has been selected to be a part of the sample they cannot be selected a second time. If multiple samples are being taken, an individual can appear in more than one sample, but only once in each sample.

Simple Random Sampling
A method of obtaining a sample from a population in which every member of the population has an equal chance of being selected
Stratified random sample
Where you have first identified the population of interest, you then divide this population into strata or groups based on some characteristic. In Jaylen’s example he would be using years of experience (for example new nurse, mid-career, and experienced) as his strata. Once you define the strata you perform simple random sample from each strata.
Cluster sample
Where a random cluster of subjects is taken from the population of interest. For instance, Jaylen could obtain a list of the nursing teams at the hospital. Each team would be a cluster. Then he could randomly select one of the teams to use as his sample.

## Convenience Sampling

While probability-based sampling methods are considered better because they can prevent sampling bias, there are times when it is not possible to use one of these methods. For example, a researcher may not have access to the entire population. In cases were probability-based sampling methods are not practical, convenience samples are often used.

Convenience Sampling
A method of obtaining a sample from a population by ease of accessibility; such a sample is not random and may not be representative of the intended population.

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