Random sampling is one method for doing market research. This is the explanation!
Random sampling is one of the most common methods in obtaining respondents to research the market. Random sampling method is one way in collecting the most famous and simple data in the field of research.
This method will allow data collection that is not biased and allows research to conclusions that are also not biased.
So, how do you do random sampling? Read on the article about Random Sampling until it’s finished.
Understanding random sampling is
Reporting from Simply Psychology page, Random Sampling is a type of collection of probability which everyone in all target populations has the same opportunity rights in choosing. This sample will be randomly selected so that the representation of the results is not biased from the total population.
Because there are certain reasons, the sample does not represent a population, the variation in the sample will experience sampling errors.
This random sample requires naming or population numbering on the target then uses several types of lottery methods in choosing those who will later be used as samples. Random samples are the best way in choosing samples from the population that are in demand.
Random sampling type
Reporting from the Towards Data Science page, there are at least four types in doing random sampling techniques, including:
1. Simple random sampling
Simple random sampling is a random selection that is done from a small segment of an individual or member of the total population.
This will later give each individual or population member with the same and fair probability level to be chosen. This simple random sampling method is one of the easiest and the simplest sample selection techniques to do.
With a sample size that is quite large, then Simple Random Sampling has a higher level of external validity because it is able to represent the characteristics of a larger population.
However, this simple random sampling has its own challenges in the process of implementation. In addition, there are also several requirements that must be met, including:
- Have a complete list of each member on a population
- Able to contact or access each population member if they are selected
- Having time and also sufficient resources in collecting data from the sample size that is needed.
- Has a complete list of population members.
Simple random sampling will run well if you have enough time and enough resources in conducting research, or if you study a limited population and be able to easily take the sample.
2. Stratified random sampling
Stratified random sampling is the taking of a multilevel sample conducted. This will include the division of the population to be subclass with differences and also a striking variation.
This sampling method will allow you to make a more reliable conclusion and also more informative because it ensures that each subcode has been represented more adequately in the selected sample.
Multi-level sampling is the best choice among the probability sampling methods if you believe that a subgroup has a different average value in the variable studied.
The benefits that can be obtained using stratified random sampling are:
- Able to ensure a sample variation
- Able to ensure similar sample variations
- Lower variations from overall in a population
- Able to divide the method of data collection.
In using this method, you must be able to divide all your populations into the most complete and exclusive sub group. That is, every member of the population must be able to be classified clearly into a subgroup.
3. Random sampling cluster
Random sampling cluster is a method that is almost similar to stratified random sampling. In it will be divided into populations into several sub-classes. Each sub-class must be able to describe the same characteristics as all selected samples.
However, this method requires random selection of all sub-class. Generally, this method is often used in studying large populations, especially those that have been geographically spread. You can use units that have previously been like a city or school as the main cluster.
Random sampling cluster is generally used because it can provide benefits as follows:
- This method requires a more efficient cost and time, especially for samples that have been geographically scattered and will be difficult to take samples appropriately.
- Samples taken using randomization will have high external validity, because the sample will reflect the characteristics of a much larger market.
4. Systematic Random Sampling
Systematic Random Sampling is a method of selecting individuals or certain members of all existing populations. This method is often done by following the interval that had indeed been determined.
This systematic sampling method is able to compare by taking samples in a simple and uncomplicated.
When taking a systematic sampling with a list of populations, it is very important to consider the order of each registered population so that you can ensure that your sample is truly valid.
If your population is in the order that is increasing or decreasing, using this method will be able to provide more representative samples, because it will include participants from the second lowest and also the top population.
However, you cannot use this method if your population is sorted into cycly or periodically. Why? Because later the sample produced becomes non-representative.
Of the four techniques above, we can conclude that the easiest technique to do is Simple Random Testing. For this reason, our next discussion will focus more on how to do simple random testing.
Steps to simplete random sampling
In doing simple random sampling properly and precisely, you must first determine the population that will be used as a target for market research. In it includes determining the demographics of your population.
Second, count the number of respondents you need. The most common trust interval and also the level that can be used is 0.05 to 0.95. If you experience difficulties in calculating the number of respondents you need, you can use the sample size calculator.
Third, do the selection of respondents randomly by deploying the survey invitation via email customers that you make the respondent’s target. Then, wait until the response you receive is able to reach the number of respondents that you have targeted.
Finally, collect all data obtained from respondents and then do a deep analysis.
When should you use Simple Random Sampling?
Simple random sampling is the way it used to obtain statistical conclusions related to a population. This will help you ensure high internal validity. In addition, Simple Random Testing has a high level of external validity in representing the characteristics of a larger population.
So, the use of Simple Random Testing has its own challenges than other random sampling. For this reason, it is recommended to use this method in the following conditions.
- There is a complete data related to a population
- Every population member can be contacted easily
- Have enough time and resources in doing so
But, if you are unable to fulfill the three conditions above, it is recommended to use the other random sampling method that we have written above.
Advantages of using simple random sampling
The main objective of the use of Simple Random Sampling is to reduce the potential for human bias in selection of cases that will be inputted in the sample. So, Simple Random Sampling is done to be a representation of a group that is not biased.
This method is claimed to be the fairest method in choosing samples from large populations, because every member has the same opportunity to be chosen. As a result, this simple random sample will give a drop that greatly represents a population that has been studied, assuming that there are limited data is limited.
Simple Lack of Random Sampling
Errors in terms of sampling can occur in simple random sampling if the sample is not carried out accurately. So, simple random sampling can only be done if the population list is available and complete. But, to be able to get a complete list of the population will be difficult for various reasons.
There is a possibility of the availability of a single list that details the population you are needed. So, it will likely be difficult and take a long time to collect many sub-lists in making the final list that the sample wants you to choose.
There is also possible population data that you need is not publicly available, so more effort to get it.
Doing market research cannot be done easily, both online or offline, you must be able to do it effectively. There are various ways of sampling that you can use from random sampling techniques.
You only need to adjust the method you want to use with the population conditions and the purpose of the market research you want to do.
So, later you can get a high level of validation and marketing strategies even more effectively to do and the company’s profits can even be more available.
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