 Okay. Good morning. I'm Sachin Patwardhan and I'm going to talk about the scientific method. The scientific method is something that has given rise to the huge scientific community, scientific culture, and today's technological society. So, when did we start? So, if I go back and look at the definition of what is a scientific method, in Oxford English Dictionary, we find this one line sentence very, very loaded actually tries to give you a gist of what is the scientific method. So, a method or a procedure that has characterized natural science since the 17th century. So, this consists of two things. One is systematic observation, measurement, and experiment. So, look at these highlighted words. Systematic measurement and experiment, systematic observations. Well, word systematic is very, very important which means somebody else can follow the same system that you are following and then verify, validate the results. The second most important part of the scientific method is formulation, testing, and modification of a hypothesis. So, the methods that existed probably before that, it have the first part, formulation, testing. But this part, modification of a hypothesis, a continued modification of a hypothesis, which keeps developing into theories is probably one of the most crucial, one of the most important parts of the scientific method. Of course, question is that when you start talking about technical communication, why do I need to talk about the scientific method? Because this is at the heart of any technical or scientific activity that we undertake. So, students who are participating in this technical endeavor have to know what is this method? What are the nuances? What are the steps? What are the features of this method? So, in this first short lecture, I'm going to just highlight in abstract way what is the scientific method. We can follow up that with examples. I'll take some famous examples and then move on to a day-to-day example and again come back to what is the relevance of this and the scientific communication, technical communication. So, let's start with the features of the scientific method. So, this method essentially builds on previously available knowledge. Well, of course, here what we mean is previously available knowledge created through the scientific method itself. So, it is not that you come up with some idea without help of what has been done earlier. The next important feature of this method is that it continuously improves our understanding of the world of the different phenomena that we observe, natural phenomena that we observe. In the process, this method improves itself. So, this is something amazing. It's not that the method is static, the method itself keeps changing, method itself is improving itself as the time progresses. The most critical aspect of this method is what we call as falsifiability or refutability. The falsifiability word appears a little difficult to understand. I think these synonyms are better to make it clear, testability of a hypothesis. You have a hypothesis that explains certain underlying phenomena and this hypothesis. To test this hypothesis, you construct certain experiments. These experiments, anyone, everyone should be able to do in principle, and then validate the hypothesis that you advanced. So, this is falsifiability, refutability, testability is the most critical aspect of the scientific method. So, what is the first thing that we need to do? The first thing that we need to do, of course, is formulate a question. Now, this is critical for any technical endeavor, whether you start doing undergraduate project, whether you are doing your master's thesis, whether you are doing your doctoral work, if you decide to write some technical paper, communication in a journal, in a conference. You are working in a company and you are given a project and you have to write a project report. So, you are working in a company R&D and then you are supposed to publish or a patent of some discovery that you have made in the R&D. So, there are a variety of forums where you are supposed to make technical reports. There could be of different significance. We'll see how these are organized, how the scientific literature is organized. Now, the next thing that is important here is, after formulating the question, is you develop a hypothesis or a conjuncture, which is falsifiable or which is testable. So, testable as in testable in a meaningful way. So, I'm going to illustrate this using simple example, what I mean by testable using meaningful way. We should be able to carry out predictions using the hypothesis of phenomena that possibly have the same fundamental cause. Again, these predictions should be testable. So, these are very important aspects of the scientific method. That is, you should first have a clearly defined question that you are investigating for your project, for whatever level of project it is. Then, you should have a hypothesis. You should have a conjuncture. You should have a fundamental explanation that you believe is playing a role in a certain phenomena. You should have a test to verify your hypothesis in a meaningful way. You should be able to carry out predictions using hypothesis, and again, these predictions should be testable in a meaningful way. So, these are critical steps when you apply the scientific method. So, what we do is once we formulate a hypothesis, a conjuncture, we actually conduct experiments to test or validate this hypothesis. Now, what I mean here by experiments would differ in different domains. It is not necessarily a physical experiment where you go to a lab and experiment could be even mathematical simulation. An experiment could be a workshop that you are conducting to test certain ideas. Let's say you are working in field of education, new different methods of teaching, and then your experiment would be actually teaching a particular subject in a different way that you have hypothesized is a better way of doing it. So, what I mean here, conduct an experiment is in a very wide sense, not necessarily using some test tubes, and it could be a workshop that you conduct, it could be a simulation experiment, it could be solving some equations that arise in the context of your. So, take it in a very broad sense, not necessarily in the context of only science. Scientific method could be applied to many disciplines even in humanities. So, then we analyze the results of experiments, and the last part written on the slide is communicate the results for peer review. This is one of the most important part of the scientific communication. Once we undertake a scientific inquiry, we do not keep the results to ourselves. We subject the results, we subject our findings to a peer review. So, who are the peers? Peers are typically experts in the area, acknowledged experts in the area. So, in different contexts, they would mean different things in a masters or PhD dissertation. This could be some faculty members working in some universities in the context of a presentation made in a company, it could be experts within the company who have been working on the particular area for many years, have gathered experience to work in that area. So, you subject your work for peer review and dissemination, so that it is open to criticism. So, this last step is very, very important and this is where you see what is the connection with technical communication. Technical communication is an integral part of the scientific method. It cannot work without people who are participating, decide to communicate their results, publish their results in different ways. So, what we're going to do is do these presentations in short modules. So, now on, I'll continue on different modules that we have created. We have four more modules on the scientific method. What I'm going to do next is illustrate the scientific method through two famous examples. I'm sure all of you know these examples. I'm going to view these examples as illustration of scientific method at work. We probably know as science students or these examples now not necessarily have to be understood by professional science professionals. These are from the schoolbook examples. So, all of us probably know these examples right from grade 9 or grade 10. So, they should cut across any discipline or any background. Now, first example is the structure of atom, and it is well known now how this evolution occurred at the end of the 19th century and then how the new ideas were formed at the beginning of the 20th century. So, let's begin with JJ Thompson, who in 1897 conducted several experiments on discharge of electric discharge through gases, through different gases. In these experiments, it was revealed that atoms of different elements have negatively charged particles. At that point of time, these were not called electrons. It was not known that these are electrons, or the word electron had not been coined. But what was revealed through this experiment was that these particles are identical for all the atoms. It doesn't matter which gas you are doing experiment with. There are identical particles which are negatively charged. So, every experiment showed existence of these kind of particles. Now, what was known by then was that the atoms as a whole are electrically neutral. So, logically, it follows that the atoms must contain positively charged particles. To neutralize these negatively charged particles, and the question that was being discussed in the scientific community at that point was, how are the protons and electrons arranged in other words, what is the structure of an atom? Okay. So, just saying that there are positively charged particles and negatively charged particles present inside an atom is not sufficient. To explain certain behavior, to explain certain phenomena that were observed, it was necessary to look at the structure, the arrangement of these particles inside the atom. Now, one of the first model on structure of atom was proposed by Thomson, and he assumed that the atoms are regarded as spheres of approximately 10 nanometer radius, carrying equal number of protons and electrons. So, this is known as plum pudding or blueberry muffin model, where have you seen blueberry muffin? In the muffin, you have lot of raisins, black raisins, they are suspended in the muffin. So, in the same way, it was visualized that the electrons are suspended in this mass of protons. So, electrons are like raisins, and these protons surround this electrons like a pudding. So, the hypothesis was that mass of protons is evenly spread over the atom, and electrons are free to rotate within this plum pudding, within this cloud of positive substance. So, what was the prediction? The prediction was that such an arrangement would lead to electrical neutrality of the atom. So, the successful prediction using this model. So, this particular model had one success, explaining electrical neutrality of all the atoms that are observed. But could it predict some other behavior, some other phenomena that were observed, which had the same underlying cause, that is the structure of the atom. So, that is the question that arose soon, because new experiments were performed, new phenomena were observed, and it was necessary to use the structure of atom to explain those phenomena. So, what were the failed predictions? So, here are some well-known failed predictions. Spectral lines known from some elements, they couldn't be explained using this plum pudding model, why you see spectral lines. And the other one, which is normally discussed in the school textbooks, is the Geiger-Marsden's Goldfoil experiment. So, which was conducted in 1909, the behavior of alpha particles observed in this Goldfoil experiment couldn't be explained using Thompson's model. So, what was this experiment? So, in this experiment, Geiger and Marsden bombarded a thin Goldfoil with alpha particles, and then they observed how these particles scatter in different directions. Now, you could calculate how the particle should behave based on plum pudding model, that is Thompson's model, and if the calculations based on plum pudding model were correct, then the alpha particle should pass through the Goldfoil without causing any deflection. Okay. So, same cause, that is structure of atom, is being used to explain a phenomena that was observed in the Goldfoil experiment. But actually, what was observed was that a small fraction of alpha particles, they experienced strong deflections. It was not that you could neglect this part, that some particles are actually showing deflection. So, Rutherford advanced an alternate hypothesis. Actually, this model is attached with Rutherford's name, but the original idea came from a Japanese physicist by name Nagaoka. Nagaoka had proposed this model, which is known as the planetary model. So, it was proposed that the positive charges in the atom are concentrated in the nucleus and electrons are orbiting around this nucleus like Saturn rings. So, this was a model independently proposed by Nagaoka in 1904 and Rutherford decided to pick this model to explain the phenomena that was observed in the Geiger-Masden experiment. So, Rutherford in 1911 developed a mathematical model based on this idea, based on the planetary model idea, and related the foil substance and thickness to the velocity of alpha particles. So, here is this mathematical relationship, which he came up with, which related the scattering cross-section with properties of the material and also the deflection angle. This is just a cartoon that shows what each model should predict. Thompson's model, where electrons and positive charges protons are evenly distributed like a pudding, should allow alpha particles to pass through as they are without any deflection. Whereas here, because the positive charges are concentrated in the nucleus, some of them will get deflected, the other particles will pass through as they are. This was a prediction that Rutherford came up with with his mathematical model based on the idea of this planetary model of Nagaoka. This is a graph that shows that the predictions made by Rutherford actually matched Geiger-Masden experimental data. Not only once, they repeated their experiment in 1913, and they could again see match between the theoretical expression developed by Rutherford and the experimental data. So, this was a strong evidence to support the hypothesis proposed by Rutherford Nagaoka and a new theory was born about the structure of atom. Of course, what happened subsequently, all of you know that even Rutherford's model couldn't explain certain behavior. For example, why the electrons do not fall into the nucleus losing the energy and so on. So, it was further modified by Bohr and then it was further modified. Now, probably we have a very, very complex model for atom. At no point, this development stopped. At no point, any of the hypothesis was considered to be sacred enough so that it shouldn't be questioned, and it continues to develop, it continues to progress. So, my second example is another famous example from the literature, that is structure of DNA. So, these five modules will be one in the beginning which I talked about, then structure of atom as a separate example, then structure of DNA as a separate example, then we have one more day-to-day example, and then closing the connection between, in the closing we talk about the connection between the scientific literature. So, this is my second example. So, discovery of DNA structure was another famous example from the literature which all of us know. As I said, the scientific method builds on the prior knowledge. What is the prior knowledge here? Well, the DNA molecules are actually carriers of the genetic information, was something that was very well known by the time Watson and Crick undertook their investigations into the structure of DNA molecule. So, experiments that were conducted by Avery McLeod and McCarthy in 1944 had conclusively established that DNA molecules are the carriers of genetic information. So, that was something which was known. Subsequent investigations had also revealed that these DNA molecules consist of four nucleotides. What are these nucleotides? Are there bio faculty here? ATGC, what is it? And cytosine. So, there are four these basic building blocks, they were also known. Okay. Structure of individual nucleotide was known, properties were known. Okay. So, the question that was being asked in the scientific community at that point is what is the mechanism of storing and transmitting the genetic information? In the DNA molecule. So, how is the information stored? Okay. Individual components are known, composition of individual components is known. Okay. How it is arranged? And this was the key to answering this question as how genetic information is stored and transmitted. So, the hypothesis that was made by Francis Crick and James Watson was that DNA has a helical structure. Using helical transforms, these three scientists, Cauchyron, Crick, and Vand, they had predicted that if DNA had a helical structure, then its X-ray diffraction pattern should be X-shaped. Okay. So, first, there was a proposal, there was a hypothesis or there was a juncture that the arrangement of these nucleotides is in a helical form, and using mathematics purely without devoid of any biological considerations. They had predicted that if the arrangement is helical, then the X-ray diffraction pattern should show certain structure. So, this was purely a mathematical construct. Okay. No biology involved. Rosalind Franklin almost about the same time, okay, came up with this experimental evidence. She crystallized pure DNA and performed X-ray diffraction on this crystallized sample. And this is the famous photo 51 in the history of biology, which transform our understanding of how nucleotides are arranged in a DNA molecule. So, this famous photo showed an X-shape, which is what these three scientists had predicted based on helical transforms, purely based on mathematical concentrations. So, looking at photo 51, Watson recognized this as a helix. And of course, what happened subsequent to that is well known to us. Watson and Crick then produced their helix model, and using the diffraction that was observed by Rosalind Franklin as an evidence, and also taking into consideration the structure of nucleotides and interaction between hydrogen bonds and so on, they came up with their mathematical model for DNA. And this particular discovery transformed the way we do the biology now. So, these are two famous examples. Now, I'm going to talk about a day-to-day example. So now, these are looking at some famous examples. Well, it does illustrate the scientific method work, but you might say we are talking about people who got Nobel Prize. So, is this for me? I mean, you and me are food soldiers of science. How does it relate to us? Why are we talking about great discoveries? So, I'm going to take a simple example, day-to-day example, and then relate how we apply scientific method. Now, the example that we have chosen doesn't require any particular background. Anyone can participate in understanding or extending this example. So, before I begin to talk about a simple example, let's just take a quick look at what are the steps involved in the scientific method. And why it's being called as a cycle. It's a cyclic process which you continuously improve. It never stagnates because you continuously improve. So, the first thing that is very, very important is that you should have an observation or a measurement. To explain this observed behavior, we advance certain hypothesis or a conjuncture. So, this is some fundamental theoretical explanation for the causative mechanism. Why you observe certain behavior? Then, we would like to use this hypothesis to predict some other behavior, which has the same causative mechanism. Then, you test this hypothesis. You actually test whether this hypothesis is correct using this prediction and a test that is constructed to validate the prediction. If the taste fails, then you go back and revise the hypothesis, and then you again go through these steps. The cyclic process, once you converge, once you are satisfied, you decide to communicate it to the scientific community. Well, let's look at a very, very simple example. Suppose in this, you enter this room, and then as you enter, you switch on your monitor. Then, you find that the computer monitor display is blank. So, I'm going to make a hypothesis. So, there is a general power failure. When I enter the room, let's say there is no light, and I just switched on the monitor first. What I find is that it's blank. So, what should be a prediction that I can make based on the hypothesis? Can somebody help me? The power is off. Prediction? Prediction. What is a prediction? Prediction is not a prediction. Sir, when the power is off, the computer will not be working. But computer is my, this is my observation that computer is not working. What predictions I can make? Other electrical appliances should not be working. Other electrical appliances should not be working. So, the prediction that I make is that all the powered equipments in this room, okay, they should be off. They shouldn't work. They shouldn't switch on. So, what is the test that you can construct? Here, check it out. So, I go back and switch on each of these. You switch on the fan, you switch on some other device that is connected lights, and well, what you found was, some of them are working, some of them are not working. Okay. So, I have a hypothesis. My hypothesis is that there is a general power failure. Implication of the same hypothesis is that all devices in the room should not be working. But when I actually conducted a test to check this hypothesis, okay, this test is switch on other equipment. I found some of them are working and some of them are not working. So, this hypothesis, yeah? So, I have to do what I have to do next. The application of scientific method means, I re-hypothesize. I go back and change my hypothesis. So, let me come up with a new hypothesis. Okay. At least one of the phases has failed. Okay. So, now just help me, what is the prediction? They will not be functioning. And what should be the test? So, you check one by one the devices which are connected on a particular phase, okay? So, of course, the particular phase is the one on which your monitor is connected. So, prediction is that all powered equipment connected to this phase are down, okay? And you go and do a test. You switch on each of these equipment and then you found that all of them are down, okay? Well, so, this hypothesis is confirmed to be true. What if let's go on this game for some more time? What happens if this hypothesis was failed? What will be the next hypothesis? Low voltage, low voltage will, will it be? No, okay. If something is working, if few equipment are working. This is a fault. This is a fault in the monitor? No. This is a single phase. Single phase. Single phase? Yes. Maybe low connection. Monitor plug is not connected properly. Monitor plug is not connected properly, okay? So, that could be or the plug. Plug in which you have plugged in the monitor, okay? That plug has failed. Not entire line, but the plug has failed, okay? So, what is the test? The plug has failed. Connect another device to the same plug and you know. So, we actually unknowingly apply the scientific method, okay? To many things that we do around, okay? And, well, we need to apply the scientific method when you do your projects, when you do your thesis, when you do your, you know, when you work on a patent or when you work on some project report. So, this is the cycle of, I think, what is extremely important in the scientific method is the experiments. The experiments are supreme, okay? And, evaluation of the hypothesis or the model is essential, okay? So, what is also very, very important is that the model or the hypothesis should be testable, okay? It should be testable. If it is not testable, then, you know, you cannot, it doesn't fall under the purview of scientific method. So, verifiable predictions, verifiable tests are very, very important. For example, somebody comes up with an explanation that aliens have taken control of the monitor. I mean, somebody can come up with that kind of an explanation. Now, the point is, if there was a way of checking this, anyone, if anyone can check this independently, that aliens have taken control of your monitor, then it could fall under the purview of, you know, scientific investigation. But if there is no way of checking this, there's no way of confirming this independently by other people, then, you know, such a test, such a hypothesis will not stand. So, tests must be reproducible by independent persons following identical procedures. So, this is very, very important. And this is also important in the context of technical communication that when you communicate, you should communicate in such a way that your test should be reproduced by anyone else. You should not omit details. You should not. So, this particular thing is very, very important in the context of technical communication. And it should be time invariant for static hypothesis. It should not be that, you know, this year, the second law of motion is not working. Last year, it was working. So, you can't have that kind of situation. So, what happens over the years is that the hypothesis, you know, are collected into models, and these models grow into a theory. So, extent of validity of a scientific theory is actually decided by the falsification test it has withstood, okay? We call something to be an accepted theory when the hypothesis, the models that are given by a particular scientific theory have withstood falsification test by a number of people in number of different contexts. Okay, so this is the concluding part of this session and also the talk that I have been giving. It's good that we had this session in between so that, you know, you are, the diagrams that I have been drawing are no longer just mere words. They would actually mean something. And the hypothesis is something that, if you reflect, you keep having hypothesis about many, or hypothesis about many things without really being an expert. I mean, when my car fails to hypothesize why my car has failed, it's not starting. I don't have to be a mechanic or I don't have to be an automobile engineer or I don't have to be automobile designer so I can come up with a hypothesis based on my prior experience about how my car has behaved in the past. Okay, maybe one hypothesis could be that the petrol tank is empty. Okay, and so on. So to come up with an explanation, come up with a hypothesis, you don't have to be a super expert. At your level, you could come up with a hypothesis and you should be able to test, you know. Okay, so I want to highlight, in this short communication, I want to highlight what is the importance of technical communication in the scientific method. Okay, so the most important thing is what happened here, okay, criticism. Okay, review criticism of hypothesis, model or theory. I just put all that levels, all the three levels. Hypothesis could be a simple hypothesis, okay. A model could be something more complex which is, you know, combination of multiple hypothesis explaining a more complex phenomena. And a theory could be something which is much more deeper. We say theory of gravitation, which explains so many different models, which can use to construct so many different models. So which after, you know, being tested by multiple people, multiple groups, in multiple contexts, you know, it sort of becomes firm as a theory. So the review of criticism by anyone at any time, okay, is the most important part. There is no the final word. There is no the expert who cannot be questioned, okay. This is the essence of the scientific method, that nothing is static, okay. Probably you might have read at the end of 19th century or beginning of 20th century where some physicists came up with things like now physics is done, okay. Now nothing more is needed to be discovered. You know, everything that needs to be discovered has been discovered. And well, you know now that all those predictions, how meaningless are those predictions. So the main thing about the scientific method is that nothing is sacrosanct. Everything is open to criticism. Okay, like you said, you know, what if Ping works? He came up with a different test, okay. Tomorrow you can come up with a different test, different, you know, the test that will, you know, gravitation theory not work, okay. So anyone is allowed to do that, okay. And except that the test you come up with, he also should be able to repeat. He also should be able to repeat. And then confirm that, yeah, by this test this is happening. That's why, you know, this cannot be expected using theory of gravitation. You need, then somebody else will come and, you know, come up with a new hypothesis and then it slowly develops. So review by peers is very, very important. People who are experts in the area, but it is not restricted to peers. Anyone can criticize, okay. Anyone can say foul, but then the person who says foul should give a logical explanation why he or she is saying it is foul or group or, you know, group of researchers. So criticism often comes from novice, okay, or budding researchers. That is because they're unconditioned, okay. Many times the criticism doesn't, why we say that, you know, the science or technology many times developed from the young minds because they are unconditioned. They are not, you know, conditioned by prior thinking too much. They can think of new options and then they try it and then it works, okay. That's how the science progresses. So what is most important is what we did just now, okay. That publishing your results of scientific investigation. The investigation that we were undertaking was, you know, coming up with an explanation for certain observation that server not responding. Something that you and me every day at least ten times, you know, get this message on your screen, server not responding. And we are trying to come up with a scientific explanation for this. So we should publish our results. Openly talk these results, okay. In form of technical projects, reports, journal or conference articles or research monographs or master's thesis, PhD dissertation patent. There are different ways of subjecting your work to criticism, okay. So this is a very, very, very crucial step in science and technology advancement. Now somebody said that, you know, what Sundar is doing is like democracy. And a lot of you laughed. Well, probably because we firmly believe that, you know, the science or technology advances because of one brilliant mind, one Newton, one Einstein. That is not true. It develops collectively by the scientific community, collective effort of the scientific community. Everyone, you and me are contributing to it, okay. So contrary to the belief that, you know, this is the media created images that there are some great minds who come and they do, of course, okay. When a war is won, we remember generals, okay. A general cannot, you know, wage a war and win it without foot soldiers, okay. Everyone is needed. Everyone who is involved in the scientific community, in the scientific endeavor, is needed to do this falsification. Test on different systems, okay. Test on, you know, you might be contributing in different ways. You might be contributing like Sundar said. You might be contributing in coming up with a modified hypothesis, defining hypothesis. You might be coming up with using existing hypothesis to test something, okay. You might be, you might be, you know, coming up with a new observation altogether. Like Rosalind Franklin, when she did X-ray diffraction, she had no clue that it is because of helix. She just wanted to do X-ray diffraction on the pure DNA, okay, and she reported. Important thing is, it wasn't kept to herself, okay. It was disseminated. It was communicated to everyone, okay. Somebody else, Watson and Crick, saw that and say, you know, great, this is what we have been looking for. This is what our prediction was, okay. So communicating results is the most important steps in the, and peer review. And who is contributing, who is doing this peer review? It's you and me, okay. We are doing this peer review when the students, you know, actually present their projects. And then you say that, okay, this is the right way of writing a report. This is not the right way of presenting your, making your presentation, okay. So you are training the scientific mind, okay, to be part of this entire endeavor, okay. And you could be doing this as an expert in some company. You could be doing this as an expert, evaluating a tech thesis or a PID thesis or master's thesis or whatever. So, or a reviewer for a journal, if you have been doing that, okay. So this is a collective process, and the science doesn't progress because of few bright minds only. It progresses all of us working together. It's a community exercise. So we have a question, and we get some interesting observation. We typically communicate in form of, you know, some research paper, like Rosalind Freud. Then there are groups, you know, maybe research scholars, there are research groups in companies who look at the literature, okay. Try to come up with some new hypothesis. Well, if you have a new hypothesis, then you should be able to predict something else. Like Sundar said, there are two important things. First of all, you have an observation, okay. Your observation should be explained by the hypothesis. And the same hypothesis, if it is used to predict something else, okay, which is testable, then, you know, your hypothesis becomes, you know, more stronger, okay. It gains more weight. And then you communicate that, okay. And well, after that, somebody else questions the hypothesis, okay. And comes up with a new hypothesis. I'll give you another simple example in two minutes. You know, most of you are here from technical background. So let me take liberty to give you an example of technical. So let's say you have this room, okay. In which, you know, I want to understand how the temperature distribution inside the room changes, okay. How the temperature, because, you know, it's important because this is the air conditioned room, okay. I want to manage my air conditioner to understand the behavior of temperature distribution inside this room. Let's say you have some, you know, three or four measurements of temperature, which are being logged in the central, you know, control room of this building. But the temperature at different, four different locations are being logged, okay. Now, I want to come up with a model, okay. So what I do, I go back and look at a literature. How such a room behavior is modeled, okay. So I come up with, I find that differential equations are used to model such a behavior. So my first assumption, my first hypothesis, is that this is like one single room, one temperature. There's a single temperature inside the room, okay. And I try to develop a model, mathematical model, for change of temperature as function of different, you know, different parameters. For example, you know, how many times the doors are opened, how many people are sitting inside, okay. I'll come up with some kind of a model that explains. So what I'll do is, based on this model, I will predict how should the temperature be, okay, based on the model, these are mathematical calculations. I'll solve some equation using properties of air, you know, and then some data about how many times the doors are opened and closed and so on. I'll come up with some predictions. I'll check whether these predictions match with, you know, the record of temperature that I have in the control. If it matches reasonably well, okay. I'll write a paper, okay. I'll write a paper and communicate it to the, communicate as in it could be for a conference paper, it could be as a thesis in your department. But when you do this, you find that, you know, the next student will come and say, well, these predictions are there, but the match is not that good, okay. Maybe assuming that, you know, this one room has one single temperature, you know, it's like one single tank is not a good idea, okay. Somebody might revise and come up and say that, well, I'll divide this room into four components and I'll model each component, okay. So I will model this room as interplay between four components, okay. You can do that and then you try to predict based on model, again check. So one can go on revising the hypothesis, one can go on revising the models, okay, and come up with new models and this is what happens, okay. So somebody questions the prior hypothesis, prior. So somebody will say, well, four sections is not a great idea. You know, I will divide this into 100 sections, okay. And then I will have tiny models for each component and then these models interact. Maybe, yeah, maybe that is a good hypothesis. So you come up with the hypothesis, come up with predictions, whether you're able to explain the data better. If you're able to explain data better, communicate, okay. And then, so this ongoing process, this is an ongoing process, which we collectively participate and improve the theory, build a theory, okay. So it is not a do-it-yourself recipe, okay. It requires knowledge, skill, intelligence, and well, creative. But more word is missing here, perseverance, okay. Probably most important word is, well, these things are important, but you also need perseverance. So the critical step is that you should be able to clearly, clearly define a question. That is the first important thing. Then go back and look at what others have done, okay. When I say what others have done, what are the other scientific investigations? What are the other investigations they're kind of using the method of, you know, the scientific method. From the literature you try to collect. Then what we do is, you know, we formulate a hypothesis or formulate a model, okay. We evaluate different research options, okay. So this is typically the sequence in which we operate. So when you give a project to your student, okay, maybe a undergraduate student or to a graduate student, you first, you know, you first define a question. Now that's where, since you have been teaching research in a particular area, you have gathered experience to define a question clearly. So that is what it is. You give a question to the student, you ask the student to do literature review, okay. So this is very, very important. Because unless there is a literature on which you can, you know, you can bank up on and see how others have thought about it, you do not make calculated cases. You cannot come up with good hypothesis, okay. So to be able to benefit from the literature, you should be able to communicate to the literature body, right. So that's why, you know, one of the most important steps is communicating the results. So to do all these things, you know, formulate a question, to be able to come up with a good hypothesis, you have to have prior knowledge or literature, okay. Once you have formulated a hypothesis, you come up with an experiment to test the hypothesis, and you get the data, okay. We analyze and interpret the data, and we validate the hypothesis. Of course, it's easy to write here. We come up with an experiment, then we get some results. We realize that well, the experiment wasn't well designed. We refine the experiment. So it's an iterative process, okay. So when you do it for the first time, maybe you yourself or your research group, you and your advisor, or you and your student, they are the ones who are, you know, doing the iterations. And the next step is, after you are satisfied, as an individual or as a group, okay, you publish these validated results, that you let others criticize what you have done, okay. So this is very, very important. This is, and the entire, you know, the scientific development and technical development thrives on technical communication, okay. So if you do not teach your students at whatever level, at undergraduate level to, you know, if you do not teach them how to communicate, okay, then that will not contribute to the progress of science. So it's extremely important that you teach them. The levels might be different. The intensity might be different, but they have to be trained in technical communication. Now this will happen that somebody will revise your hypothesis, somebody might revise your model, somebody might revise your entire theory, okay. Anyone is allowed to do that. This is typically learned by somebody else, okay. And you shouldn't feel sore about it, okay. So if she proposes some hypothesis, and somebody comes up with an explanation that contradicts, somebody comes up with a test that contradicts the hypothesis, fine. In the spirit of scientific inquiry, we should accept and move forward, okay. That's important, okay. But at the, you know, surface of scientific development, what is happening is exactly what happened in this room sometime back, okay. Nobody's sure. People are proposing different hypothesis. You comment upon somebody else, some other group's work and so on. So what are the common pitfalls, you know? Well, this happened in this, just reflect. Did this happen? Yeah. Assume that the hypothesis is an explanation. So this is a common, this is another thing that you will always hit upon, you know. Either when you are doing research or whether you see your students coming and reporting to you. It is very, very often in the first, so I have a master student or a PhD student, in initial phase of his or her telling, they only tend to report good results, okay. They know what will make the guide happy or the supervisor happy, and only those results are reported. The results which are actually going against, you know, the hypothesis advanced by the supervisor are not reported. Actually what the student doesn't understand, a beginner doesn't understand, is that what the supervisor has given you is a calculated guess. Probably he has been into that area for a long time, or he or she has been in that area for a long time. They are able to come up with a good guess. It could very well be wrong, okay. So if there is an evidence which is showing that this hypothesis is given by the supervisor, there is wrong, you should present it. That is the spirit of scientific development, okay. So we tend to ignore what we don't like, or what we think the supervisor will like, okay. And the other common problem is failure to quantitatively estimate errors in the measurement, okay. You have some erroneous measurements. Any measurement that you take is subject to, okay, there are different kinds of errors. There could be random errors. You could repeat the multiple times and write around the random errors. The other kind of errors are systematic errors, or the background errors. And these background errors could be actually pointing out to something more deeper, okay. It could be pointing out to a missed, you know, cause or some explanation. So ignoring errors, either systematic or even random errors, okay, can lead to wrong, you know, conclusions that you come up with. So these are some of the references that you can look at. So the initial part that we talked about was taken from this popular source, which is Wikipedia. But the other references are at different levels. Sundar, do you want to say something about this? Yeah. Where you will get more insights into the scientific method. So about a technical communication post-lunch, we will continue about technical communication and the link between the communication skill. So what we did after this, after the lunch, is reading skills, okay. What is the connection of reading skills, reading literature with the technical communication.