 So let's start with a new topic that is sampling design, how do we make a sample for our study? So we have basically two type of sampling that is probability and non-probability. If this is your population, you make a small sample from it. So how do you conduct this process is known as sampling. If you are conducting a study on medical students, the whole medical students of that particular college will be your population. That will be around 1000 or 2000 or 5000. So you are making sample of 100. So how you make this 1000 to 100 without losing its property is known as sampling design. So we have probability and non-probability sampling. So always probability sampling is better compared to non-probability sampling. I am just giving you now the difference, different types. In the next class I will explain you in detail each one. So in probability, the first one is simple random sampling, that is SRS, simple random sampling, systematic sampling, first one is simple random sampling, systematic sampling, the third one and fourth one, third one is stratified sampling, fourth one is cluster sampling, multi-stage sampling, non-probability is convenient sampling. This is most common one used in our study but this is what done in RCT or experimental study. So basically the difference between probability and non-probability sampling is, the chance of being in the study is equal to all the population for probability sampling and non-probability the chance of being in the study is not common or equal for all the participants. If suppose we have a population of 1000 people and we are making a sample of 100 out of it, here all the 1000 participants has equal chance of being the 100. If you are making 1000 to 100, now all the participants will not have the chance of being in 100.