all right hello everyone um yeah I would like to welcome you to our second lecture um all right so in the previous uh lecture we um talked about uh a few types of bias samples um keep in mind we said a bias sample is a sample that shows favoritism to one out outcome than the other um in the population uh we talked about about a convenience sample as a buyer sample and we said that a convenience sample which is generally sample where um information is collected just as it is easy for you to get it is uh by a sample because take for example if you simply collect information only from your friends people who are who are hospitable to you then that would not represent uh the opinions of people who are not friendly to you are not your family members okay so we also talked about our voluntary response sample and we said that's also a bio sample because when it it is up to the subjects to decide whether to participate in your study or not then only those who have some kind of strong interest will be willing to participate and show your sample will not represent the opinions of all um of all um um um individuals in the population okay good so that is a bio sample now we're going to look at the um um the t uh sampling technique which is actually a simple random sample now that is denoted uh as RS okay and we will talk about a simple random sample of size and subjects all right good um now um just one second let me okay so when we talk about a simple random sample of size um n now the question is what do we mean by um n good so um if you consider say for example this is your population right here okay and this population has a size now we would generally denote the population size by capital n for example maybe if that is Georgia s then your capital N will be maybe 27,000 students good now when you generate a sample out of this population then uh what we denote the size of this sample by small n for example we can have that our small n can just be maybe 3 students okay good okay now what do we mean by a simple random sample of size n okay all right um now we are going to Define a simple random sample of size n just one sec okay now if we go back to what a simple random sample is all right of size n it is defined as um as a kind of sample generated from a population where every sample of n subjects has an equal chance of being selected okay so um let me try to explain exactly what this means okay all right so if you have that population right here and if you oops um one sec okay now um if you consider all possible samples of size and say maybe that is sample one um maybe this is sample number number two and so on Sample number three whatever sample number that is all possible samples of the same size n n for example maybe your n is equal to 200 same thing n n n then all of oops right all of this examples have an equal chance chance to be selected good so a simple random sample of size N is a sample that is generated from a population in such a way that every sample of the same of that same size n will have an equal chance to be selected now um let me say that one easy way to um generate a simple random sample um let's say from uh if you want a simple random sample of students in a particular class okay then um you can simply write your names down on um on on some uh t ticket or cards and you put it in a you can put the cards in a basket and then you mix thoroughly and you randomly uh choose five of them okay for example if you want a simple random sample of size and equal to five now that is going to give you a simple random sample it is actually just a sample where every individual in the population will have an equal chance to be selected okay okay now the next slide uh how do you create a simple random sample in practice now uh you have to be patient uh with me as I'm using some new equipment over here um so I'm still learning to um maneuver my way to um the different applications okay all right so let's see exactly how we create a simple random sample all right so in practice to uh oops okay all right so in practice you uh you want to look at exactly how we uh create a simple random sample okay good so the first thing we have to do is we have to uh label the uh subjects in the population okay good so um generally if we have say a population size of so if you have a population size of say n equal to up to 100 then we are going to lbel using uh 0 1 0 2 and so on when we get to 99 then we go on to 0 0 now if you have a population size of up to say 1,000 uh subjects then you have to use uh three digit levels 0 0 two and so on up to um 9 N and then you have 0 0 0 and so on okay okay now um the next step to be able to uh generate we use a random number table random uh digits random digits which we can get from our random number table which is given to us in table B all right so um I believe at this point you must have downloaded your um tables um and if you flip back you're going to uh find um table B now let me pull one over here so we can take a look at okay now um here is um the first couple of rows from your um table B okay now um let's try to understand exactly what this um um table is trying to describe okay all right so um um what you have here is just a string of u a single string of numbers starting on from um where you see the line 101 as you go on this first row you get to this last number on the last column and then you continue all along like that it's just one long string of numbers starting on from 101 going all the way down okay good now um each of these um numbers are randomly uh generated by the computer okay so exactly uh what the computer does is that um you see we have um oops uh one second okay all right so so the computer all right will randomize all of these digits um from 0 1 2 3 up to eight and nine so they are all together 10 digits okay all right so the computer randomizes all of this meaning that will mix them all properly and then randomly choose one and it happens that that first number that comes out is one so each of these numbers are generated in such a way that every um every one of these entries has an equal chance to be um selected okay and um so to get the next one computer will randomly mix all of this uh meaning that makes it all properly and then select the second one which is going to be um the nine