Sampling > Non-Probability Sampling

## What is Non-Probability Sampling?

Non-probability sampling is a sampling technique where the odds of any member being selected for a sample **cannot be calculated**. It’s the opposite of probability sampling, where you *can *calculate the odds. In addition, probability sampling involves random selection, while non-probability sampling does not–it relies on the subjective judgement of the researcher.

The odds do not have to be equal for a method to be considered probability sampling. For example, one person could have a 10% chance of being selected and another person could have a 50% chance of being selected. It’s non-probability sampling when you **can’t calculate the odds at all**.

One major disadvantage of non-probability sampling is that it’s impossible to know how well you are representing the population. Plus, you can’t calculate confidence intervals and margins of error. This is the major reason why, if at all possible, you should consider probability sampling methods first.

## Types of Non-Probability Sampling

**Convenience Sampling:**as the name suggests, this involves collecting a sample from somewhere convenient to you: the mall, your local school, your church. Sometimes called accidental sampling, opportunity sampling or grab sampling.**Haphazard Sampling:**where a researcher chooses items haphazardly, trying to simulate randomness. However, the result may not be random at all and is often tainted by selection bias.**Purposive Sampling:**where the researcher chooses a sample based on their knowledge about the population and the study itself. The study participants are chosen based on the study’s purpose. There are several types of purposive sampling. For a full list, advantages and disadvantages of the method, see the article: Purposive Sampling.**Expert Sampling**: in this method, the researcher draws the sample from a list of experts in the field.**Heterogeneity Sampling / Diversity Sampling**: a type of sampling where you deliberately choose members so that all views are represented. However, those views may or may not be represented proportionally.**Modal Instance Sampling**: The most “typical” members are chosen from a set.**Quota Sampling**: where the groups (i.e. men and women) in the sample are proportional to the groups in the population.**Snowball Sampling**: where research participants recruit other members for the study. This method is particularly useful when participants might be hard to find. For example, a study on working prostitutes or current heroin users.

would you please add advantage and disadvantage of nonprobabality sampling

You’d have to look at each individual method, as there are quite a few and they are all different. For example, see a list of advantages and disadvantages for purposive sampling here: http://www.statisticshowto.com/purposive-sampling/

Would you compare and contrast each of them .

Hi, Ami,

There are 7 different methods listed, so to compare and contrast each of them would be 21 different comparisons! In addition, purposive sampling has an additional 7 different types to compare and contrast…That would make for a very long blog post :).

Some of the comparisons can already be found on the individual pages.

Was there a specific comparison you need to make instead?

What is your last name Andale how ill i be able to use u as a citation for my paper work???????

Stephanie Glen :)