non-probability sampling

The Digital Revolution

In today’s world, it is hard to deny the fact that we are living in a revolutionary digital age. For a variety of reasons, the internet and other forms of modern digital technology have taken the world by storm and have forever changed the way that we interact with one another, transact business, and generally go about our daily lives.

As with any major piece of technological advancement, there are both upsides and downsides to the digital revolution. On one hand, it is easier than ever to access information and to communicate with people from around the world. Get a question about the history of a certain country, for example, and it can be answered in minutes with a simple Google search (or, depending on the complexity of the query, a few hours). Many believe that the influx of information found online has enabled people to become better informed, more educated, and more sophisticated overall.

On the other hand, it is hard to overlook the downsides to this digital revolution. The bad can range anywhere from the explosion of internet bullying to the overall bombardment of “info overload” that can leave us feeling fatigued and disenchanted with the massive world that we suddenly have right at our fingertips.

It is also worth noting that the digital revolution has dramatically altered the commercial space, particularly in terms of what is and what is not possible to do with the internet. From shopping to banking and much more, almost all of the aspects of our consumer lives have moved online – enabling us to do many things that would have otherwise been impossible.

While the digital revolution may have some drawbacks, it is safe to say that on the whole, it has enriched our lives and made the world that we live in that much better. From gaining access to new and exciting forms of entertainment to being able to access almost any type of information with ease – the digital revolution truly has changed the way that we look at the world around us.

Non-probability sampling is a type of sampling methodology used in research that does not rely on random selection of subjects. It is a sampling technique used when it is either impossible or impractical to use random selection. Instead, special group of subjects is chosen depending on various criteria such as availability, convenience, cost, or location.

The main advantage of non-probability sampling is that it allows a researcher to target specific types of people and investigate them more closely. However, one of the biggest drawbacks is that the sample may not be representative of the population. This is because it is harder to determine the sampling frame from which to select the sample and the same people may not represent the population as a whole.

In addition, non-probability samples are more time consuming and more challenging to analyse. For example, in non-probability samples, the researcher may need to determine the sampling frame, meaning the researcher first needs to decide who or which items constitute the population.

Non-probability sampling is usually used by researchers who want to find a specific group of individuals or items to study. This type of sampling can be useful in investigating a small subset of the population. For example, researchers might want to investigate a certain age group or investigate a specific region.

In conclusion, non-probability sampling is a sampling method used in research when it is impossible or impractical to use random selection. This can be useful in investigating certain groups of people or items. However, drawbacks include difficulty in determining a sampling frame and potential non-representative data. For this reason, researchers should always evaluate the potential drawbacks of using non-probability sampling.