Advantage and Disadvantage of Sampling
Sampling:
Sampling is a process used in statistical analysis in which a predetermined number of observations are taken from a larger population. The methodology used to sample from a larger population depends on the type of analysis being performed, but it may include simple random sampling or systematic sampling.
How Sampling Works?
First of all, we have to choose the basis of sampling, i.e. the rule that will determine whether a sample is chosen or not. After we are sure of the method which will be used for the process, you select the samples as specified in the previously set plan. The method used for choosing the samples as the very name suggests, is the most crucial part of the whole process, it defines whether the analysis accurately describes the entire population or not.
Characteristics of the sampling technique
- Much cheaper.
- Saves time.
3. Much reliable.
4. Very suitable for carrying out different surveys.
5. Scientific in nature.
A representative sample needs to have the same characteristics as the target population. For example, if our target population are children 6–59 months living in a pastoralist population, our sample needs to contain children 6–59 months who are living in this same population. The distribution of age and sex and other characteristics in our sample should be very similar to the distribution seen in the target population. Having a representative sample also means that:
1. Each individual or sampling unit in the population has a known, non-zero chance or probability of being selected.
2. The selection of one individual is independent from the selection of another. Since we are only collecting data on a sub-group of the population when sampling, it is important to remember that the result obtained will only be an estimate of the indicator that needed to be measured. As discussed above, to get the true value, it would be necessary to conduct an exhaustive survey.
Probability Sampling Methods
The main types of probability sampling methods are simple random sampling, stratified sampling, cluster sampling, multistage sampling, and systematic random sampling. The key benefit of probability sampling methods is that they guarantee that the sample chosen is representative of the population. This ensures that the statistical conclusions will be valid.
· Simple random sampling. Simple random sampling refers to any sampling method that has the following properties.
· The population consists of N objects.
· The sample consists of n objects.
· If all possible samples of n objects are equally likely to occur, the sampling method is called simple random sampling.
There are many ways to obtain a simple random sample. One way would be the lottery method. Each of the N population members is assigned a unique number. The numbers are placed in a bowl and thoroughly mixed. Then, a blind-folded researcher selects n numbers. Population members having the selected numbers are included in the sample.
Stratified sampling: With stratified sampling, the population is divided into groups, based on some characteristic. Then, within each group, a probability sample is selected. In stratified sampling, the groups are called strata.
For eg. : Suppose we conduct a national survey. We might divide the population into groups or strata, based on geography — north, east, south, and west. Then, within each stratum, we might randomly select survey respondents.
Stratified Sampling
Cluster sampling: With cluster sampling, every member of the population is assigned to one, and only one, group. Each group is called a cluster. A sample of clusters is chosen, using a probability method (often simple random sampling). Only individuals within sampled clusters are surveyed.
Cluster sampling
Systematic Clustering: Here the selection of elements is systematic and not random except the first element. Elements of a sample are chosen at regular intervals of population. All the elements are put together in a sequence first where each element has the equal chance of being selected.
Systematic sampling
Systematic random sampling: With systematic random sampling, we create a list of every member of the population. From the list, we randomly select the first sample element from the first k elements on the population list. Thereafter, we select every kth element on the list.
This method is different from simple random sampling since every possible sample of n elements is not equally likely.
Advantages and Disadvantages of Sampling:
Advantages of Sampling:
Sampling have various benefits to us. Some of the advantages are listed below:
· Sampling saves time to a great extent by reducing the volume of data. You do not go through each of the individual items.
· Sampling Avoids monotony in works. You do not have to repeat the query again and again to all the individual data.
· When you have limited time, survey without using sampling becomes impossible. It allows us to get near-accurate results in much lesser time
· When you use proper methods, you are likely to achieve higher level of accuracy by using sampling than without using sampling in some cases due to reduction in monotony, data handling issues etc.
· By using sampling, you can get detailed information on the data even by employing small amount of resources.
Disadvantages of Sampling:
Every coin has two sides. Sampling also have some demerits. Some of the disadvantages are:
· Since choice of sampling method is a judgmental task, there exist chances of biasness as per the mindset of the person who chooses it.
· Improper selection of sampling techniques may cause the whole process to defunct.
· Selection of proper size of samples is a difficult job.
· Sampling may exclude some data that might not be homogenous to the data that are taken. This affects the level of accuracy in the results.
For example: It’s used in situations of highly sensitive topics like HIV Aids where people will not openly discuss and participate in surveys to share information about HIV Aids.
Not all the victims will respond to the questions asked so researchers can contact people they know or volunteers to get in touch with the victims and collect information helps in situations where we do not have the access to sufficient people with the characteristics we are seeking. It starts with finding people to study.
