Types of Sampling Methods
A sampling method is a way to find out what the opinions of a large amount of people are by surveying a small amount of people. This can be useful is conducted correctly, but can result in skewed data if not conducted correctly. For example, if the surveyed people have not been picked at random or if they have been picked in a way that poorly represents the entire population, you will get skewed data.
The sampling method is a way to find out what the opinions are of a large group of people by just surveying a small amount of people. The sampling method can be useful if it’s conducted in the right way, but it’s not conducted in the right way it can result in skewed data.
So there’s a couple of practices that result in skewed data. One practice is not picking people at random. If the surveyor handpicks the people to talk to then it’s not at random, and so it’s not going to give a good indication of the population as a whole.
Second problem, is when it poorly represents the larger population. This happens when only one group of the larger group is interviewed. Say for example, that you’re interviewing everyone in the United States of America.
Well, what could happen is that you only interview people in Nebraska. You may pick people at random within the state of Nebraska, but you’re leaving out the other 49 states, and so it’s poorly representing the larger population because you’re not getting people from all different areas of the U.S..
Now in order for the data to be representative of the population as a whole it has to be picked at random. The people surveyed have to be picked at random and it has to represent the population as a whole. It has to do essentially the opposite of what we listed earlier.
I want to give you a couple scenarios of the sampling method, and we’re going to decide whether this is a good way to go about it or not. A town wants to gather opinions of residents, so it interviews a random group of residents from each street in town.
This is a great way to go about it. Remember, it has to be at random. It says that right there. It’s a random group of residents and it’s from each street in town. Because what would happen here, is if you just interview a random group of residents from the city you might leave out people from certain sections of the city.
But, by making sure it’s random, but also making sure you get people from each street in town, you are getting a better idea of the opinions of the town as a whole. Now, the second scenario is a clothing store has a target population of people ages 15 to 35.
It wants to get an idea of the opinions of its customers. It interviews, or surveys, customers that are 15 to 16 years old. They may have just picked these 15 to 16 year old customers at random, so they may have gotten the random part right, but the problem is they left out all the people 17 to 35 that are also part of the target population.
They did not represent the population as a whole because they didn’t get people from other age groups. They just limited it to kids 15 and 16 years old. This is an example of skewed data. In other words, the surveyors that used the sampling method to get opinions of the customers at the store are going to come up with skewed data because they did not go about their surveying in the correct manner.