 So, looks like some centers people have come and some centers people are still trickling in. So, I request you to raise your hands in the software and then we will take some interactive questions now before going to the next tutorial. So, we have M.E. Society Pune. Hello M.E. Society Pune. Good afternoon. Sir, this question is for Patwardhan sir. Yes, please. You can sit down madam. While explaining hypothesis prediction S10 result, he had said prediction is also an observation as to what else can happen. That's correct. So, can it be implied that prediction is in a way what we are going to test as far as the test is concerned? Yes. See for example, if you take power failure case, if you take that power cable has failed, then I could predict that using this power cable, another monitor will not get powered. So, that's an observation that you expect to happen. If this positive mechanism is true that the power cable has failed, if this is a fundamental causative mechanism, the power cable has failed. So, what other prediction you can make using this fundamental causative mechanism? If you use this power cable to power some other device, some other monitor, then that monitor also should not switch on. Then you can perform that test. It has to be other than, see, your monitor has failed, monitor in front of you has failed. Now, I am coming up with a test which is an observation with respect to some other monitor, not with my monitor. If the power cable has failed, then using the same power cable, some other monitor also should not get switched on. Okay. I have not performed the test. I am just predicting. This is what will happen if I use the same power cable. This is a prediction based on now actually connecting the power cable to another monitor. What is the test that you perform? But see, what is important that you have to see here is that without even having to perform the test, I am predicting what should happen using the basic causative mechanism. Do you get the point? If I say that the power cable has failed, then, you know, the same causative mechanism will not permit you to switch on some other device if the same power cable is used on that device. That is the prediction. And then, you know, you can actually test the prediction by taking the power cable, connecting it to some other device and seeing whether that other monitor is switched on using the same power cable or not. So, power, so it could be an observation that is, that you predict should happen based on, you know, the same causative mechanism. See, even in the example in our slides, we had said that, you know, a particular phase has failed. You know, what other observation that you can predict if the phase has failed? Some other device connected to the same phase has failed. That is a prediction. It's an observation, right? So, before even performing the test, I am predicting if the phase has failed, then, you know, the printer that is connected to the same phase also is not working. And now, then I can go and perform the test. I can switch on the printer and check. The printer is not on. Then, I have a proof that, you know, my hypothesis that a phase has failed is able to explain something else, not just my monitor is not switched on. The printer is also not switched on. Something else connected to that. We can perform one more test. We can have two more predictions, three more predictions. Everything, every device connected to the phase is not, you know. So, then you can go and test every device. Yeah? Is it clear? Yes. Hello. Yes. I have made one example. As you said, of the power cable, based upon it, I made one analogy. My observation is that no current is turning out to the classes. The hypothesis, maybe there may be a spike in the campus. The corresponding prediction may be in all the departments of the college. There is no student in the class. That is correct. My test may be called for, I can call for. That is sufficient. Usually, in the small problems that we are considering, the prediction and test are very close. Like the question that was pointed out by the previous college. So, what you said is right. Now, if there is a strike, strike will lead to no persons in your classroom. Strike will lead to also no persons in any other department's classroom. So, you are correct. So, your hypothesis explains two different observations. One, which has already been observed. Other, is a future observation, which we calling as prediction. Okay. Thank you very much. K. L. Institute of Technology. Hello. Hello, sir. Good afternoon. We want some example for scientific model, sir. A more scientific method of research, whatever you have explained. Taking an example of physics field. Can you explain it using some other example? I think the time will be little too short for that. In fact, if you take any, any, what the point we are trying to make here is, any application or any research article that you read is all this. So, that was what presented in the last thing. How is your scientific method actually related to what you communicate? So, anything that you communicate in a paper is essentially an observation. Some people just do experiments and report it. So, that is an observation. So, if you take any journal paper, if you see that it is purely experiment, there is no explanation of any further causative mechanism. They are reporting only the observation part. Now, some papers might not have any experiments, but somebody else would have done the experiments. They would have tried to explain it. So, they explain it by writing a set of equations. So, when you write a set of equation, that equation is actually your hypothesis. It is your model. So, that model will explain certain things. It will explain something else also. So, anything, so there is no one example. There are millions of examples. Any paper that you take is essentially one form of expression of this scientific method. So, the reason why we brought this topic here is whenever we are communicating something, we should know in what aspect of the scientific methodology that we are communicating. Are we communicating only the observation or are we communicating a new hypothesis or we might be even disproving an existing hypothesis. So, these are all part of a day-to-day activity that is happening everywhere in all research universities and research labs. Okay, we will go to the next college, PSG college. Thank you very much. Hello, good afternoon PSG. I am the workshop coordinator of this PSG Tech. And regarding that, the hypothesis development, sir, is it possible to have the results without having proper analysis of the prediction? Yeah, so you are saying that is it possible that you report some results without advancing any hypothesis or causative mechanism explanation. Yeah, that is quite possible in some situations. One famous example in the recorded set of lectures, I have talked about diffraction pattern of DNA, X-ray diffraction pattern of DNA. So, when Rosalind Franklin actually published her work, it was just an observation. She did not propose any model. She just observed a particular pattern when she did the, you know, studies and she just published it. Probably there was no fundamental causative mechanism why it happens. So, that came from Watson and Crick independently. So, it's possible that sometimes you have an interesting observation which nobody has seen before and you want to communicate it to the community. It's important that there might be other people who can probably provide an explanation hypothesis or causative mechanism. But you just have an interesting phenomenon to report. So, you know, the same thing is about Geiger Marsden experiment. They did not, they just reported their observations that when alpha particles are bombarded on a gold foil, you find some deflections. They did not provide any causative mechanism why it happens. So, somebody else came up with, you know, explanation as to why this happens. So, it's important if you have an interesting observation, it's important that you report it. Yes, you need not always come up with a hypothesis. So, of course, if one hypothesis comes to explain it, somebody else comes up with a better hypothesis and the prior one gets, previous one gets rejected and so on. So, that can happen. Thank you, PSG. Thakur College of Engineering. Hello, Thakur College. Good afternoon, sir. Sir, my hypothesis for that monitor blind case was monitor is switched off because of damaged switch. So, because of that I have got a prediction that all other devices which are connected to that particular computer, according to that particular computer, they will work more normally which are not connected to that switch. So, is the prediction correct over here? So, you are saying the switch, the plug point, the switch that has failed, correct? Yes, sir, only the switch has failed. The plug point and all would be correct that we don't know about it. Only the switch is not working properly, that is what my hypothesis is. So, how will you come up with a prediction based on the switch? So, I have come up with a prediction that all other devices of that particular computer will be working properly except the monitor. Oh, you mean the switch inside the computer? Or the monitor? Power switch, power switch of the monitor. The power switch of the monitor is faulty. Yes, sir. So, you mean there is just like this, we have what is it called the extension board. In that one of the switches failed, is that what you are saying? Yes, sir, we can consider that as well. One of the switches failed. Okay, the switch that is kept on the monitor has failed and other devices connected to the computer. Basically, there are two switches, one is for the monitor and the other one is for the CPU and for other devices which we can also configure with it. For my example, only the monitor switch is not proper, it is faulty. Okay. In that, I have the prediction that the CPU would be working properly. Fine. So, this is similar to the example that was said, like a general power failure or the phase. Fine. So, in that sense, it is... Yes, sir. Right, your prediction at least is consistent. It is consistent with the hypothesis. Okay. Thank you. Okay. So, now I think most of the colleges have come. We are going to reset this questionnaire session and we are going to continue with the modal discussion. Now, in the modal assignment, we had given a small problem which is like very similar to this monitor display failure. The problem was that you are waiting in a bus stop. Normally, you take a bus from the bus stop and every day, it comes on time. But this one particular day, the bus has not come for more than 15 minutes, which is very, very unusual. And we were asked, you were asked to come up with three different hypotheses and three different predictions. So, this is what we explained there. The observation that is bus has not come on time. Okay. You are waiting in the bus stop. So, just as you do a research question, you have a question here. Why does... Why hasn't the bus come on time? The answer to the question is essentially your hypothesis. Now, whether the hypothesis is true or not, you need to come up with prediction. Just to recollect what we said there, hypothesis is a causative mechanism of two different things, one which has been already observed, one which is yet to be observed. Okay. So, the yet to be observed thing is called as a prediction. Okay. So, now what we are going to do is to show you examples from what you have submitted. Okay. We are going to take several examples from what you, several people have submitted. And what we are going to ask you to do is to critically look at it and say what is the problem with that. It is very similar to the peer assessment that you have done. In peer assessment, you are given five different hypothesis that others had submitted and you had given them an evaluation. Now, what we ask you to do is to do it now in front of everybody and give the reasons of why you think a particular hypothesis is correct or wrong or why a particular prediction is right or wrong, is it consistent like the way we discussed for this display failure. Okay. So, we will take one example now. So, this example, I am not sure if everybody can see it. I will read it for you. Let us take the first hypothesis. Now, again we will do the same think-par-share. I am going to read that hypothesis and prediction. After that, you are going to think for yourself and write down your criticism of it. Either you accept it that it is good or bad. If it is bad, you have to give some reasons. If it is good, you have to probably explain why it is good. Okay. So, first one minute you spend time with yourself, write it down and then you discuss with your neighbor and then we will take up randomly some centers. Okay. So, the hypothesis reads as follows. The bus has not come possibly because of heavy rain yesterday. This is the hypothesis. So, first thing that you have to do is whether the hypothesis explains the current observation. There are two things that has to be done. Whether hypothesis first explains the observation. If it fails here, then it is no use proceeding further. First of all, it should explain this. Then you should also see first of the prediction whether it is a real prediction or it is something like a solution like many of us have come up with. It should be a prediction and that prediction also should have the same causative mechanism. Okay. So, I will go to that. The bus has not come possibly because of heavy rain yesterday. Due to traffic caused by heavy rain and bad roads created by it. Okay. So, the heavy rain created heavy traffic and bad roads. So, that is the prediction. So, take about a minute. Think about it and write your criticism of this answer. Okay. So, let us take questions now. Perumal, Mani Meghalaya College. Sir, the predictions given here has not tested with some other examples. No. Okay. First, let us see whether the hypothesis is right. So, do you think the hypothesis explains the current observation? No, sir. Scientifically not explained, sir. But it explained but not scientifically. One minute, one minute. No. There is nothing to the whole of, what do you mean by scientific? If you undergo this process of hypothesis, prediction and testing, then it is scientific. You cannot decide it is unscientific even before you starting to do it. So, the first thing. Hypothesis is right, sir. First thing about scientific is whether the hypothesis explains the prediction. Now, if you say it does not explain, only then it is called unscientific. Otherwise, it is still part of scientific. It is still not completed but it is still scientific. So, as long as you are following this methodology, it is scientific. Okay. So, when we say something is scientific reasoning, it is essentially following this sequence of steps. So, let us answer this question first. What did you or your partner feel whether the hypothesis explains the observation or not? Yes, sir. It explains. It explains. Okay. Very good. So, your partner also agrees with that. Yes, sir. So, the bus has not come because of heavy rain yesterday. Now, the prediction was due to traffic caused by heavy rain and bad roads caused created by it. So, is this prediction okay? No, it is not scientifically told. It is not scientifically told. What do you mean by that? That means due to traffic caused by what is called bad roads, other buses should also come late. Are you correcting or providing a sentence or so, I think what you mean is. I am explaining that. Okay. So, this particular sentence is first of all not written well okay. I think what the author meant was why the bus has not come. In the prediction, the author has given answer to a question why it has not come. It has not come because of the bad roads created by the rains okay, but this is not a prediction at all. It is also some kind of explanation. It is also another hypothesis. It is not a prediction which has got the same causative mechanism as hypothesis okay. The prediction is an answer to the question why the bus has not come which is essentially another hypothesis. It has not come due to heavy traffic caused by, due to traffic caused by rain and bad roads. So, this is not a prediction at all okay, okay, so sorry we will take one more college now 1 0 8 0 Kugat Perli, yes, so first of all you have to tell whether the hypothesis explains the observation and then whether the prediction is a valid prediction. So, in the first example that was stated, the hypothesis is either correct but the prediction is not, given near example or an explanation for the reason but it is not a prediction at all. Okay, very good. So, that is we have discussed very good, so we will go to the second example. Here the hypothesis is the bus has not come possibly because of big breakdown okay that is the first statement prediction is if there would not have been a breakdown the bus would have come in time. The reason we have taken this particular example is the people who evaluated this gave it a very high score 1146 knowledge institute over to you please. Hello sir. Hello, very nice. Am I audible? Can hear you. Sir, actually that is correct. Sir, which is correct. The prediction is correct sir. The first example that is. The first example or we are talking about second example? Second example sample X3. Sample X3, very good. So, it is a prediction. It is a prediction actually. If there would not have been a breakdown then the bus come on time. Yes sir. Okay. Did you write this? No sir. No sir. Okay. No. I am not. Okay. So, why do you think it is right? Because he does not give the exact solution. The solution, it may be predictable, that is if it not breakdown then it will become on time. So, that is the thing. You see. He is not giving the exact solution for that. So, can you rewind the time, go back and check this observation, is it a testable prediction? Yes sir. It is testable. So, you can go back in time, is it and then actually the bus will come in time, is it? No sir. No. See, is it a prediction first of all? Is it, is the statement a prediction? It is also another, it is a part of the hypothesis only. If there is no breakdown, the bus would have come on time. Why has the bus delayed? The bus is delayed because of breakdown. This is basically restatement of the same hypothesis. It is not a independent observation that you can go and test it out, ok. The bus, what is hypothesis? Hypothesis is an explanation of an observation. The bus has not come because of breakdown. Prediction is also the same. If the bus, if there would not have been a breakdown, then the bus would have come on time. This is essentially a restatement of the same hypothesis. It is not an independent observation, alright. So, let us look at the second example. The bus has not come on time possibly because of traffic jam. Again the same thing. It would, the bus would be on time if there was no traffic jam. So, these are not prediction. It is a restatement of the hypothesis, ok. So, what would be a prediction? See, if the bus has not come because of the traffic jam, you could predict some other bus which is supposed to come at the same time, that also should not arrive. That could be a prediction. But here what is stated as a prediction is not a prediction. It is just a restatement of the hypothesis. So, prediction should be about some other phenomena which has the same causative mechanism. If traffic jam is a causative mechanism, what else it will, what else you can predict based on this causative mechanism? Not just buses, maybe you can say that no traffic is coming. So, there could be different predictions, not a single test. There could be multiple test based on the same causative mechanism. But what is given here is not a prediction. Ok, let us take one more from here. The bus has not come possibly because there is heavy raining in Islampur, ok. That is the hypothesis. If there is heavy raining in Islampur, then satellite image should show clouds on Islampur. So, we will go to 1, 2, 1, 7, graduate school of technology, yeah. The hypothesis does support the prediction, sorry, the observation. Yes, very good. The first thing that you need to look at is whether the hypothesis explains the current observation. Very good. So, you have said that right. Yes, and the prediction also kind of supports the hypothesis because satellite images would be the other observation where it would kind of confirm that there is heavy raining going on. Yes. So, the same causative mechanism which is heavy rain also leads to, I mean, also leads to an observation of a cloud, correct. So, if there is. Yes. In that, so, now suppose you go and look up the satellite image and you find, you can, so this hypothesis is testable. You go and find the satellite image. If there is cloud, ok, you can be reasonably sure that your hypothesis is right, ok. So, very good. Thank you very much. We will go to the next hypothesis. The bus has not come possibly because it got punctured, ok. So, the prediction is if it got punctured, then I should get a call from office colleague travelling by the same bus from its start. So, we will take this from Home Institute of Technology. Sir, I have a question. What are the similarities in hypothesis and observation? Hypothesis and observation, there are no similarities. Hypothesis is an answer question of something related to the observation. So, it is usually why something happens, how something happens and so on. It is an answer to the question. You observe something, it leads to you to a question. An answer to the question, a possible answer to the question is called a hypothesis. You call it a hypothesis and not a definitive answer because you have not yet confirmed it. So, hypothesis is a possible answer to a question that came out of your observation. Hello. So, this is what was. One more question, sir. What are the importance of hypothesis in daily life? The question is what is the importance of hypothesis in daily life? So, it is as important as you think scientific method is to your daily life. If you think you ought to analyze things in a scientific spirit or scientific way, the steps that were discussed, the four steps that were discussed hypothesis, prediction, test are the cycle of steps that follows an observation. So, if you think you want to solve problem scientifically, then this is a way that is followed. You have to hypothesize why it happens that does not stop there. Just by giving a reason does not mean you have explained the observation. The reason has to also lead to something else which is observable and that something else that is observable, we call it as a prediction. So, we will take the next question from Sushila Dhanchand College. We were interested in answering the question that is hypothesis is correct and prediction is also reasonably relates to this. So, you are talking about the second one, correct? The bus has not come because it has got punctured. And it got punctured, then you should have got a call from your prediction also from the colleagues. They are traveling from the starting point and that can be testable, I mean if they are not calling, I can call them and confirm it, fine thank you. The sample Y3, I hope you all can see hypothesis one is the bus has not come possibly because of heavy traffic due to an accident on the road. The hypothesis is accident on the road. The prediction is if bus is in heavy traffic due to accident on road, check for diversion roads if available, take diversion and reach the destination in time, okay. So, I will wait for a few seconds for you to raise your hands, okay. If Francis Institute has an answer, sir of all the hypothesis given it seems they are not correct because it is more like offering possible solutions instead of giving a proper prediction. Hold on, hold on, are you talking about the hypothesis or the prediction? Let us take the first hypothesis, first tell us whether the hypothesis explains the current observation. The bus has not come possible because of heavy traffic due to an accident on road that is right. That is correct. So, the prediction is given the current situation, very good. But as far as the prediction is concerned, it is asking for checking for diversions which will be more like a solution than giving a proper prediction, okay, very good thank you. Yes, we will go to Amrita School of Engineering. Sir, the prediction is wrong, the hypothesis is right, okay. The prediction is the answer they have given. What is the prediction then? What have they written here? The prediction is, prediction what they have predicted is wrong, it is the solution for the hypothesis they have given. Exactly. So, this is how to avoid, if this was the case, how to avoid it? Sir, if the prediction, yeah, so there is a solution they have given, the prediction should have been, if the, because of the tire puncture, someone should have called us from the bus whom we know or there must be a traffic jam in the road, maybe that will be the prediction. Okay, not traffic. If it is a college bus or something bus which we know, some of the colleagues would have called us, that would have been the prediction or the observation what we have to give. Alright, thank you very much. You are right. The answer to the prediction what they have given is the solution. Yes. You are correct. Your analysis is correct. Thank you. Okay, this is sample M2. The bus has not come possibly because the schedule time of the bus is revised. Okay. So, if the schedule time of the bus is revised, then there should be a change in the timetable of the bus at the head office. KIT College of Engineering, please go ahead. What do you think of this hypothesis, is the hypothesis right? And is the prediction consistent? hypothesis number 1 seems to be okay. What about the prediction? prediction also. Is that a prediction at all? cannot be called as a prediction because the change in timetable schedule available at the head office is an availability. No, but is that, will that happen if the first thing happens? The prediction is something that will happen if the hypothesis also happens. Will that happen? If there is a rescheduling of the timetable, then there will be a copy of it available in the head office. That is correct. So, the prediction is consistent with the hypothesis. Okay. Let us look at hypothesis 2, we will go to NRI Institute of Information Science and Technology. The observation given supports the hypothesis, I am talking about last one. Yes. You are talking about this one, hypothesis number 2. Yeah, traffic jam, as the prediction is consistent with the hypothesis given. The prediction is, first of all is the prediction, is it the prediction at all? Yeah, it is observation about the hypothesis. Correct. So, it is a prediction and the prediction is consistent. It is consistent with the hypothesis. Out of the hypothesis. Okay. Yeah. Very good. Thank you. So, we will go to another example, sample X1. The bus has not come possibly because nothing, if the tire of bus has punctured then bus has not come on time. Obviously, there is no hypothesis here and the prediction is not a prediction. It is a hypothesis statement. So, we will not go to this. Sample Y1, the bus has not come possibly because of procession of Ganesh Festival on its way. Prediction, if the procession is on the same route, the next bus should be delayed but it arrived in time. Okay. So, who wants to go for this? Hello, Walchan. Please display the second hypothesis here. Okay. So, hypothesis is based on the observation because we would see the, if you know the Ganesh Festival is on, then prediction is also correct. Yes, we can hear you. So, what about the prediction? Is it a correct prediction? First of all. Prediction. See whether it is a prediction and then see whether it is consistent with the hypothesis. Yes, it is consistent with the hypothesis. Okay. Why do you think so? Because there are processions always during the Ganesh Festival and it is likely to be, I mean we can definitely attribute the next bus coming late because of the procession. So, is it a correct statement of prediction or it should be, some part of it should be removed? Just look at it critically. Should the prediction contain the last five words? But it is. But it arrived in time. But it arrived in time. Should it contain that? Yes. That should be contained. No. You see, had the sentence stopped with, if the procession is on the same route, the next bus should be delayed. That's all. Full stop. Okay. Absolutely. That is a prediction. Now. I want to ask one. You go and do the test and the outcome of the test is whether it came on time or it was delayed. That is comes a later. That is a test and carrying out the test and outcome of the test. But what is given there is not entirely correct. First part portion of the sentence is right because that explains the, that is one of the observations that is possible with the same causative mechanism. The next bus will be delayed. That is an observation which needs to be done. Now you need to go and observe it. It's a prediction in that sense. I want to ask you one more question. The mistake, we just want to explain the mistake here. The mistake here is that the test result is also combined with the prediction. They should be separate. The prediction stops at, if the procession is on the same route, the next bus should be delayed. Full stop. That's where the prediction should stop. Then comes the observation based on the prediction, whether the bus came in time or not, the second bus. And if it arrived in time, you are rejecting the hypothesis. So the way it is stated right now is incorrect. Only the first part is correct. The last part which gives you the test result should not be part of the prediction. So hypothesis is correct. Part of the statement of the prediction is correct. But if you take the entire statement, it is not a correct prediction. Because it includes result of the test. That is not a prediction. Prediction is, if there is a Ganesh procession, the next bus also should not come in time. That is a prediction. Event has not occurred. What is the result of the event is the next thing. That is the test. The test result should not be clubbed with the prediction. So the first example is not a correct example. The prediction is that prediction is wrong. That is not a way to write a prediction, in which the test result is combined with the predictions. Let's take the next hypothesis. Hypothesis number two, the bus could not come possibly because of some accident on its way. The prediction reads, if there is an accident on its way, the poll is immediately make some arrangements for the vehicles to pass, so as to avoid inconvenience to the public. So LDRP Institute of Technology. From my point of view, the hypothesis is correct. For the bus has not come possibly because of some accident on its way. But the prediction is not good. Not prediction should be there. It's not correct. Does it stand as a prediction? Hypothesis is correct. Prediction is if there is a heavy accident on its way, all the buses from that route are delayed. We ask you to tell us whether the second statement, the prediction, is it a prediction at all? It's not a prediction. It's not a prediction. Then what is it then? It shows like a case result or solutions of the hypothesis. It is like somebody trying to fix some, the police are trying to divert traffic. First of all, you don't know whether that is the reason. So that is not right. Thank you very much. Sir, I also had one question. Yes, go ahead please. Sir, what is the difference between scientific methods and methodology? No, it's just the same thing. Methodology is the process of doing it. That's all. Thank you, sir. Thank you. What we will do now is we will take some general questions from you. So this Bharati Vidya Peet. Okay, the third prediction coming to, because of red alert, strict checking of vehicle is going on. Into this case, the prediction hypothesis will be, if this bus will get delayed, other buses onto the same route will also be delayed. Okay, now are you saying that this current thing is right or wrong? No, the prediction which is given is not correct. Okay, why is it not correct? Actually, the language is not clear. Media works so as to make people alert to avoid the situation of crisis in the city. Simple thing, if the strict checking is going on of all the vehicles, then if the first bus gets delayed, the other buses onto the same route will also be get delayed. Correct, thank you very much. Symbiosis, you have a general question or you want to discuss something from here. Symbiosis, hello. Is any specific word limit, or word limit is there for defining hypothesis and prediction? And is any specific keywords we can use for the same? Thank you. What is your second question? Specific keywords. Yeah, second question. Yeah, is any specific keywords we can use for defining hypothesis and prediction? So, I will repeat the question. The first question is there word limit for the stating hypothesis? The second question are there any specific keywords that can be used as part of the hypothesis? So, the examples that we have considered are very trivial examples. Now, the reason why we took such very trivial examples are twofold. One is to help you understand what are the different aspects of scientific magic. What is not clear to many of us when we come across this first time is what is the meaning of prediction, what is an observation, what is a test and so on. So, that is the reason we took a very, very simple example and also the examples considered in the class were also very simple. That is one reason. The second reason is help you to use scientific methodology even in simple situations. Even in simple situations where you are trying to troubleshoot something in your house, Wi-Fi is not working, TV is not working. How can you go about in a scientific way? That is the reason we chose very, very simple examples and that is why your explanation, sentence are very simple. Now, what actually hypothesis means in a journal article? What does it mean in normal journal articles? People do not write one sentence like that. The whole paper could be a hypothesis. The whole paper could be a derivation. Somebody would have written a model and the whole paper they would have given derivation of that. That is itself a hypothesis. The whole paper could be stated as a model. So, then that becomes a hypothesis. So, there is nothing called a word limit or expression even in word. It could be completely mathematical. So, that is one aspect. The second aspect that there is any keywords, obviously there is no one set of keywords. It depends on what you take to explain that. That is all. G.H. Roysoni Institute of Technology. Hello. Yeah, go ahead. Sir, it is necessary in scientific method for production. Production is necessary. The question was, is it necessary in the scientific method to have a prediction? Yes. The answer is yes, it is necessary because if a particular explanation that you give explains only one observation and does not explain anything else, then it is most likely not correct or most likely you are missing out on the actual explanation. Which is why, so when Prof. Patwardhan told about falsifiability, it is essentially this. You have to come up with a testable prediction and that prediction should be such a way it can be made false. One possible outcome can be a no answer as well. You cannot have this one in which you cannot test it or always you will get an answer yes or something like that. So, prediction is a part of it. It is always essential that you have something different other than what it explains, the hypothesis. Okay, thank you so much. D.Y. Patel. Hello. Yeah. Hello sir, good afternoon. Yeah, good afternoon. Go ahead please. Yeah sir, the workshop. Yeah sir, workshop experience was very nice sir. Just one query I have, we are on a learning stage sir. So, why the peer assessment had been done by us, not by the expert? Whatever the assignments we have submitted, the correction work should be done by the expert. So, we actually come across with the, no, the proper conclusion that we, where we were lacking, where was the problem, where the, whatever we understood that is the correct or not sir. The whole problem is the numbers. We cannot handle 3000 people in numbers. The similar way that you cannot handle a class of 100 students. You cannot possibly correct the hypothesis and give feedback on 100 students. Now, the reason why we have this session is essentially to make for it. In from the, see what you learnt online is only part of the entire learning. So, there you are exposed to certain ways, certain things that you try to do it yourself and in this session we are taking examples from there and then showing to you how to look at these things and this will hopefully help you in taking your own class. So, when you, your own class, we encourage you to do a similar exercise of peer evaluation and then take a few examples. Now, if everything is going to be told only by the teacher, the students will not learn. The students will not be able to criticize others for what they have done as a mistake. So now, we want you to go back and look at whether you did correct evaluation of hypothesis of others hypothesis and secondly, you should go back and look at whether you have proposed correct hypothesis. Have you given correct predictions? You should question now. That is the reason we are openly discussing many answers, sample answers that we have received. So that, you know, you learn from the way we criticize or way others criticize and understand whether what you have done is correct or wrong. Yeah, because 3,000 students and 3 hypothesis each, you know, you can look at the number. It's very difficult to give personal feedback to each one. So, this is one other method that IT-enabled solution has given us which is the online peer evaluation. So, if you have a large class, particularly teachers who are taking a communication skill for the entire college, for example. In IIT Bombay, we run this course twice every year. Every semester we run it once and each time we have about 700 students. So even for a class of 700 students, it's just impossible. Forget 700, even 100 students each with 3 feedback is just impossible. It is just pointless. Instead, if you are able to show your students some examples, you ask them to do a peer evaluation and then you pick out a few examples just as the way we have done. Pick out a few examples and discuss in the class and then they will be able to appreciate and when they do it a second time or the next time, then they know what to look for in the answer. So, it's 2.40 now and we have to take a 5-minute break and we'll come back and take up listening skills after the break. Thank you very much.