By

Palak Jain, II year of Bachelors in Arts (BA) from Lady Amritbai Daga College for Women of Arts, Science and Commerce (LAD COLLEGE)

Introduction

A progressing nation such as India, having approximately 138 crore people residing in it needs to have proper guidance for the country to work accordingly and help people to have basic needs and necessities. Every country consists of the number of people of a different colour, religion, region, gender, status, etc., but all have their basic requirement and have a particular expectation to be fulfilled by the state. These individuals also make a pair, a small or a large group. Similarly, the groups are also frequently made according to different criteria, such as, farmers, employees, a formal group of people in a seminar, a classroom of students etc by which they are distinguished and divided. These criteria or similarities make a group special and different, from the other people. The individuals which make a large group are called “Population” of that particular space and a part of that population is called a sample in the statistical sense.

Concepts explained

In statistical terms, a population is something which allows statistics to exist, as if every population enables it to be studied thoroughly and begins its journey by dividing itself into several groups known as samples. Every population can be divided into numerous samples having a homogeneous and heterogeneous set of individuals i.e., same or different people.

For instance, sample A is having where n is the total number of females, and a sample B having,. . . . . .., where m is the total number of males. So, this is an example of homogeneous individuals. Similarly, if we have a group of black people and white people also divided according to the gender we can see that we have a sample C as, . . . . . . . . . and so on. It can be seen that the sample have males as well as females as they have been differentiated concerning the colour and not the gender, and this can be called as a heterogeneous sample as it contains differentiated cases.

These two types of cases enable us to gather as much information as needed for thoroughly working on it. Every time a population can’t be a way out for the survey and that’s why a small group known as the sample is taken from that population. Every sample is gathered by different types and it helps in the calculation of many things and provides many assumptions which help the country in its development. For instance, taking a small group of farmers as a sample from the population, their farming ways, their livelihood, their salaries, the rate of suicide a farmer commits in a day, and many other things could be predicted. Similarly, a small sample can be taken from the population of middle-class people which can be divided as lower middle class, middle class and upper-middle class. Many calculations can be made from these small samples instead of taking a huge population to explain the trend of population.

Parameters of a Sample

A sample if taken following similar criteria will be much helpful to conduct any type of calculation. For this, we survey the sample and collect the information of the sample given by the population. The first survey was conducted in 1950 in India as part of the union budget and after that, the country started to take surveys every year. Similarly, the collection of the information of the population of India is called a census which is conducted every 10 years in the country. As going towards the calculation of the things it should be known what is the average of a particular sample called as mean and also what is the spread of the population called as a variance. These two calculations are called the parameters of the population on which that particular population depends.

Similarly, to calculate the sample mean and variance, its parameters are used as same as used in population. The method to calculate the population’s parameters with the help of the sample’s parameters is known as sampling. Sampling is a great tool if have to dealt with a huge volume of data and have limited resources and therefore there are many conveniences of sampling such as it saves them time by reducing the volume of data and also it avoids the monotony in works and therefore data handling issues and other issues perceive a higher level of accuracy when proper methods of sampling are used.

Surveying without using sampling becomes impossible at a limited period. It allows for nearly accurate results in less time and also detailed information of the data can also be received by sampling methods even by employing a small number of resources. Since every coin has two sides, therefore, it also causes hindrances in the ways such as there exist chances of biases as per the mindset of the person choosing it; as sampling is a judgmental task also an improper selection of sampling techniques can cause the whole process as providing incorrect results. Since only homogeneous data don't have to be taken in the sample which implies to give a non-accurate level of result and as such difficulty also arises in selecting a proper sample size(n) and because of these limitation sampling is divided into two types - Probability sampling and non-probability sampling.

Probability Sampling

Probability sampling is defined as follows that it is also known as random sampling or chance sampling and utilizes random sampling techniques and principles to create a sample. This type of sampling method gives all the members of a population equal chances of being selected.

For example, if we have a population of 500 people, each person has a chance of 1 out of 500 being chosen for the sample. The superiority of this method is that it is Cost-effective, Judgement is of lesser degree. This is a lot easier as compared to the other sampling methods and It also consumes less period. It is being favoured as Non-technical people can also do it and also this relies more on research findings and Sample representative of the population. Contrarily, the drawback and obstacles of probability sampling are that Chances of selecting the specific class of samples only, Monotonous and Redundant work, Higher complexity and it can be more expensive and time-consuming.

Types of Probability Sampling

Since there are numerous restrictions therefore there are four types of probability samplings known as:

1. Simple Random Sampling

2. Stratified Random Sampling

3. Systematic Sampling

4. Cluster Random Sampling

These four types of sampling can be described by taking examples of job interviewers and the employees arriving for that interview.

Simple Random Sampling

Supposedly, 30 students sit for an interview for the college admissions and all thirty have different complexity, religion, status etc., but the interviewer decides to randomly pick any of the students not being partial towards anyone with a probability of 1/30. This type of random selection is known as the simple random selection and selecting a sample by this method is known as simple random sampling. This type of sampling method is also used in selecting a lottery. It is the most basic type of sampling method and is the easiest one to be used. It guarantees a sample being random without any biasedness.

Stratified Random Sampling

The second type of sampling method is known as stratified random sampling which is defined by taking an example of 500 people sitting for an interview and the interviewer is somewhat biased and partial to less educated people. The interviewer will divide the people and ask them to sit in 5 different groups of 100 people without homogeneously combining people. From these 5 groups, the interviewer will pick 20 people each, and therefore by this method, we will get a random sample of 100 people. This method is also known as “random quota sampling”. These 5 groups of 100 people are known as strata of this population and therefore it can be said that the sample is being selected from the strata divided by the given population.

Systematic Sampling

Thirdly systematic sample will be exemplified by there are around 10,000 people will be an interview to get 1000 people for a specified job then every 10th person would be selected from these 10000 people. The selection in this particular type of sampling is done by taking a periodic interval to pick people randomly as every 10th person will be chosen for the job by taking an interval, known as sampling interval when the sample size is 1000. It is suitable for researchers because of its simplicity.

Cluster Random Sampling

Finally, the fourth type of sampling method where the population is being divided into the small group known as clusters having homogeneous characteristics and features but internally these are heterogeneous. For Example,1000 people are taken as a population for an interview and 100 groups of 10 people are made with them being homogeneous but internally the 10 people also have some differences. The advantages and merits of this sampling method are that it requires fewer resources and is more feasible, but in contrast, its demerits are as the sampling error is high and it is a method having biased samples and this type is known as Cluster Random Sampling.

Mankind has practised various types of probability random sampling and in the contemporary world human beings generally use computers as a mechanism to produce random numbers and it is known as stimulation of numbers, that is producing numbers randomly by giving a specific interval to the computer. These days everything has become easier with the help of the new technology which makes humans more effective and therefore numbers have become easier to be produced and calculated.

Conclusion

To run a country with all the defined principles and habitats the most essential element which is compulsory for every situation is having a hypothetical presumption of the actual conditions of the humankind. The key to the representation of the population and various types of difficulties which are being faced – is sorting the individual irrespective of the social aspects, as a sample of the whole community through society at large cannot be examined. A sampling of particular data at vastly can be hectic as well as confusing activities but as an outcome can lead to many advantages towards the economy. Here, the representation of the country cannot be analyzed on the individual perspective contrary to this different method of sampling that is used by the government for finding the partial variable of the discussion.

As the biggest downfall of the economy can be considered as recurring an individual - as a sample for the study of the condition of the whole country but even the census which occurs by the supervision of the government also executed after 10 years of the research part. The main agenda of performing the surveying can even lead to biasness and partial data of fact as the main characteristics which a society consist is dynamic so, precisely the information which can be fluctuating. The unit of the economy which ultimately forms by the individual – if closely examined, it can lead to accurate results of the obstacles.

Conveying the probability of resources which can be substituted with technology and growth also have sampled data in it, to know whether the machinery, new modern technologies, any products which are been used as a basic necessity and any accessories which are compatible for the general public, cannot be implemented or launched without having any types of the sample within the society. Finally, concerning the basics of sampling and its uses in this contemporary world. Every space irrespective of their size needs to have an organized sector to calculate and conduct surveys and census for the development of that space and to know the condition of that particular region.