Consecutive sampling is a common method of data collection used to study a specific group of individuals. It's an efficient solution to generate data that can be used to represent a larger population. As one of the simplest sampling methods to follow, it doesn't require too much-sophisticated equipment or software.
You might wonder why it's also referred to as convenience sampling. The reason is that politically and geographically speaking, it's easy for researchers to access the people being studied.
In this article, we will highlight the importance of consecutive sampling, its advantages, and its disadvantages.
Consecutive sampling is defined as a non-probability sampling technique whereby samples are picked by the researcher at convenience. It is sometimes confused with convenience sampling but they are not the same. This technique can be used to obtain information or opinions from people or a target population without having any prior information about them.
There are various types of sampling that can be applied to statistical sampling. One of the most common non-probability sampling techniques, referred to as consecutive sampling, is often characterized by convenience for both researchers and respondents, who are also referred to as research subjects.
Consecutive sampling is a research methodology in which people, things, or events are not chosen from a larger population on the basis of whether they are statistically representative. This method is used to reduce bias or by researchers who wish to collect data quickly and easily.
Also, you can use consecutive sampling to select a sample at convenience and then determines other characteristics such as occupation, race, sex, and age. The number of people in a particular group depends on the degree of comparison.
For example, if a researcher need to collect data from 25 men and the researcher is interviewing them at the mall, the researcher will start with the first man standing in front. After that person has been interviewed and his data is collected, the next man standing will be chosen. This continues until all 25 men are interviewed, their responses are recorded and analyzed.
The convenience of conducting a consecutive sampling study is that you don't have to worry about whether or not your sample is representative of the population. Convenience samples are very popular in research because they are so easy to create.
For example, a researcher who wants to interview people currently staying in a hotel can approach each person who exits an elevator or enters the hotel lobby and ask them if they would like to participate in the study. This method is sometimes used by market researchers to gain feedback from consumers about products.
You can easily find examples of them in everyday life, such as a survey conducted at a sporting event asking people about their favorite hot dog toppings, or a poll by the local newspaper asking people where they like to go for vacation. In some cases, all you need to do is be in the right place at the right time and you can find your sample!
Here are some examples of consecutive sampling that will help you better understand the technique and its application.
A researcher wants to analyze the effect of eating snacks with a soft drink. The researcher can start off by conducting research with a set of people who are standing in line to pay for soft drinks and then, go ahead and select people from anyone who is standing or around at that time.
Let us assume that you are a teacher in a classroom full of students and your job is to measure the heights of all the students in the class. To achieve this, you are going to ask every student to stand up, one at a time.
Then, you'll measure their height and record it on your clipboard. Once you've measured the first student, you'll ask the next student to stand up and take another measurement.
The process will continue until all of the students have been measured. This is consecutive sampling.
You may be trying to poll people at a store about their favorite type of cookies. When you see someone coming in, you proceed to ask them if they want to participate.
If they say yes, then you add them to your sample group. If they say no, then you look for the next person to come in who meets your criteria for polling and ask them.
Let us assume that your company sells soap bars and wants to determine the quality of customer service in their stores. As this is a simple task that doesn't require any specialized knowledge, you decide to send your interns to the stores and have them perform the customer satisfaction survey.
You have 100 stores in your city and want to survey 20 of them (which means 20% of all stores). So you send two interns on a Saturday morning (Saturday is chosen because it's usually one of the busiest shopping days) to do the survey. They head over to the first store on their list and start surveying customers by asking them a couple of questions about their current shopping experience at the store.
When they are one with a customer, they proceed to another customer. They do not have to come up with pre-listed names. They will only conduct the survey consecutively based on the customers available and willing to participate.
Consecutive sampling is a great way to get the most out of any sample size. When you randomly select a sample from your target population, you have no idea how well that sample will represent the whole population. But when you use consecutive sampling, you can guarantee that your sample will be as representative as possible by selecting every nth person.
Let us look at some of the examples of consecutive sampling techniques.
Here are some disadvantages of consecutive sampling.
Convenience sampling (sometimes known as availability sampling) is a specific type of non-probability sampling technique that relies on data collection from population members who are conveniently available to participate in the study. Convenience sampling may involve subjects who are compelled or expected to participate in the research (e.g., students in a class).
Convenience sampling is used when researchers use their judgment to decide where to obtain data for the sample. It is often used by researchers to get a preliminary understanding of an issue or problem before applying other sampling techniques.
Consecutive sampling on the other hand is a non-probability sampling technique. The researcher selects the sample units from a population in the order in which they appear.
The researcher’s decision to select or not select a unit is based on whether it belongs to the population of interest and whether it has not been included in the sample before. Both of these sampling techniques are similar and often used interchangeably, but the difference is that consecutive sampling tries to include all accessible subjects as part of the sample.
Also, convenience sampling selects research participants based on availability while consecutive sampling selects participants according to how they meet the criteria for the study till the sample size is obtained.
The major difference between consecutive and purposive sampling, is that consecutive sampling is based purely on chance, while purposive sampling is based on the knowledge and experience of the researcher.
Consecutive sampling is a sampling method where the first subject that meets the inclusion criteria will be selected for the study. If the second subject also meets that criteria, he or she will also be included, and so forth.
Purposive sampling is a non-random form of sampling, where researchers seek out people who possess specific characteristics for their study. The researcher will “purposely” select subjects based on his or her prior knowledge, expertise, and experience.
The two are similar in that they are both non-probability sampling strategies; however, consecutive samples are only used when all individuals in a group meet specified criteria.
Consecutive sampling is generally considered to be useful when other methods of sampling are unavailable. The main advantage of consecutive sampling is that it does not require any preliminary work; it simply uses the first n cases that happen to come along. Its main disadvantage is that no randomness is involved.
If any systematic differences exist between early-occurring and late-occurring cases, the sample may not be representative of the population. In addition, if the case rate varies over time, the sample may not be representative of the population even if case timing is entirely random.
This method is often used in studies that involve rare populations, such as a specific disease or disease state. Consecutive sampling can also be used in situations when researchers are interested in investigating a rare phenomenon or event.
This type of sampling is also called maximum variation sampling because it seeks to capture all possible variations within the target population. This type of sampling technique may also be used when the researcher wants to examine specific characteristics in a group of people based on the passing time (e.g., students attending college over a period of four years).
One example of an application of consecutive sampling is when a survey team has only one opportunity to reach respondents such as while they pass through an airport security checkpoint and no information on how many people will pass through on a given day. In this situation, researchers can use consecutive sampling, selecting every nth person who passes through the checkpoint that day.
Consecutive sampling is an important concept that researchers should consider when conducting surveys. It provides a way for researchers to improve the representativeness of their samples. So if your target population is spread across a large geographic region, consecutive sampling may be a great option for you.
You may also like:
In a time when data is becoming easily accessible to researchers all over the world, the practicality of utilizing secondary data for ...
Coefficient of variation is an important concept that allows you to predict variables within and outside data sets. While it has its roots ...
Cluster sampling exists because of the complexities that come from dealing with a large population. A target population is an important ...
Measurement variables, or simply variables are commonly used in different physical science fields—including mathematics, computer science, ...