 Welcome to my channel, I am Arpita Karwa and in this video lecture I am going to talk about sampling and different types of sampling used in research methodology. But before we talk about what is a sample, it's important to understand it with the help of example. So there's a girl called Meera. Now this girl Meera, she is extremely excited to research on how stress impacts examination in the life of college students in India. Now if she wants to research on this topic, she needs to talk to each and every student of India who is in the college. Is it practically possible? I don't think so. So this girl Meera has to choose a few students on which she is going to research and then on the basis of the research she is going to develop a finding, she is going to draw a conclusion and this conclusion can be generalized on all the college students of India. Now entire college students of India, they are known as population in research methodology. But since we cannot research on the population, we take help of a sample. But a sample sample is a group of people chosen from the population on which the research is conducted and the results produced by the sample is generalized on the population. So this is known as sampling. Now there are various ways in which Meera can choose the sample and now in the next section of this video I am going to talk about different types of sampling. So when it comes to sampling, there are basically two kinds of sampling. One is probability sampling and one is non-probability sampling. What is probability sampling? Let's first understand it. Probability sampling is when the researcher chooses sample randomly from the population. So in 10th standard, you must remember that there was a chapter called probability. In probability chapter, there was randomization. There were a lot of questions asked on if a dice is thrown randomly. What is the probability that one is going to appear? So one by six is the probability. So probability is very much connected to randomization randomly. Okay, so probability sampling deals with choosing sample randomly from the population. So there are different types of probability sampling. We are going to look at them one by one. The first kind of probability sampling is simple random sampling. Now what is simple random sampling? The most easiest type of sampling. If I want to do research on all the schools of Jaipur and see how much is the stress level of the students of 10th standard. Now being from Jaipur, I know that there are in total 55 schools. Now it's not possible for me to go to each school and then collect the data from all the 55 schools. So what I do is that I decide to go by simple random sampling. In sareh schools, ke jya students hai unki list mai leke aati hoon. And then from that list, randomly I select a few students on which I'll be conducting my research. That is simple random sampling. If you take an example from your life, then lucky draw hum karte hai, that is a perfect example of simple random sampling. Apne chit dal di and randomly apne kuch logon ko choose kar liya. The second type of probability sampling is systematic random sampling. Now what is this? In this, I'm going to make a list of all the 10th class students from all the 55 schools and then I'm going to choose every nth person, every nth student. For example, I choose every 10th student. I made a list of all the students. I listed all the students alphabetically. Suppose there are 8000 students in Jaipur who are in 10th standard. Now from that 8000 students, I choose every 10th student, 10th, 20th, 30th, 40th. So this is what is known as systematic random sampling. The next kind of probability sampling is stratified random sampling. What is stratified random sampling? In this, I'm going to divide these 8000 students in homogeneous groups. So I'm going to make suppose 80 groups out of these 8000 students and from each group I'm randomly going to select a few students and on those students I'm going to conduct my research. This is stratified random sampling. Then next we have cluster sampling. Cluster sampling means you choose a naturally existing cluster and then you do your research. So rather than choosing students from 55 schools, I randomly chose 5 schools and I started doing research on these 5 schools and then I'm going to generalize it on all the schools of Jaipur. And fifth is multi-stage random sampling. Second sampling is when I randomly choose clusters and from those clusters I randomly choose students. So when I charge schools randomly and in schools, I pick randomly students. This is multi-stage. It is involving two stage. First I'm doing cluster and then in cluster I'm again doing sampling. I'm choosing a few students from that school also. That is why it is known as multi-stage sampling. So now we move on to the second type of sampling which is non-probability sampling. Till now we've discussed different types of probability sampling. Now it's time to look at what is non-probability sampling and looking at different types of non-probability sampling. So non-probability sampling from the word itself you can understand it is when you choose a sample deliberately and not randomly. You are not randomly choosing, on the basis of knowledge and experience you are deliberately taking a lot of people into your research. That is non-probability sampling. There are three main types of non-probability sampling. First is quota sampling. Now quota we all know in civics we must have heard this term. Quota is a person stage which is reserved for a particular section of society. For example 51% female quota that means 51% seats are reserved for females. So demographically the quotas are taken according to the sampling groups that is called quota sampling. For example if 51% females are there in India then you are going to take 51 females in your research. So rather than randomly choosing males and females for a research you are deliberately choosing 51 females and 49 males. This is quota sampling. The next is judgmental sampling. Quota is judgmental sampling it is evident from the term itself when you are becoming judgmental. When you are using your knowledge your past experience to select the sample that is judgmental sampling. So agar mujhe lagta hai ki mere research mein kai log apt hai ush research ke liye ush me participate karne ke liye I am deliberately going to choose them. For example if I am researching on the effect anger has on my health I am deliberately going to choose certain people I know who become angry in their day to day life very easily. So this is judgmental sampling and the third type of non-probability sampling is convenience sampling. Convenience that means I choose sample which is readily available. Jo mujhe conveniently available hai mai un logon pe research kalleti hoon rather than going out and choosing people from different places from different backgrounds. So conveniently jo log mujhe mil rahe hai I can choose them and I can do my research. This is convenience sampling. Okay so these are the three main types of non-probability sampling that you must remember if you are preparing for UGC net paper one. Before I end this video I would also like to talk about what is sampling error. Now let's first understand sampling error. Sampling error basically means that the result that you have taken out by researching on a sample differs from the result of the population. That means that apne jo research kari hai sample ke upar usse jo result nikal ke aaya hai wo result population ke case mein true hold nahi karta. I'll give you a very simple example. Suppose I want to research on who is more happy. People who are in job or people who are doing their own business. I take a sample of 200 people, 100 of them are in job and 100 of them are doing their own business. When I research on these 200 people I analyse their happiness level. I figure out that people who are in jobs are more happy. Now this is a result which I have taken out from my sample. When I use it on the population I might find that it differs. Duniya mein generally agar aap dekhenge to aap ye paayenge ki jo look business mein they are more happy than people who are in job. Now there's a difference in what my result shows when it comes to sample and what actually it is when it comes to population. This is known as sampling error. Aur ye kab hota hai sampling error is maximum when you take a small sample size. Aap ne 20 logopayi research kari. To ho sakta hai aapki findings incorrect ho because there is a chance that wo log ho sakta hai job kare ho but they are more happy. Maybe if you take 200 people who are in job you might find out that no most of the people who are in jobs they are unhappy. Now jitna chhota sample size oga utna zada ye error hone ke chances hai. So sampling error decreases with the sample size. So agar sample size aapne kam liya hai to sampling error zada hoga and agar aapne sample size bada liya hai to sampling error kam hoga. So they are not directly proportional but they are indirectly proportional. So now that we have looked at sampling main types of sampling and what is sampling error it's time to look at previous year papers and figure out if there are questions which are asked from this particular section. There were a lot of students who kept on asking me that ma'am please tell us some previous year questions with the topic you are covering so that we can have a glimpse on what kind of questions we can expect in the paper. So this is what kind of questions you can expect from the section that is sampling and types of sampling. So that's it for this video lecture. We are going to meet very soon in the next video lecture. Also if you have not subscribed to this channel do it now because I post videos every Saturday to help UTC Net aspirants in their exam preparation. Apart from that if you have any suggestion any doubts you can put that in the comment section below. You can also follow me on various social media platforms and you can also share this videos with your friends so that they also get benefitted with these video lectures. So that's it for this video lecture. We will meet soon in the next video lecture till the time we meet next. Happy learning. Keep loving literature and stay tuned to ArpitaKarwa.com.