 Good afternoon and we are off to go. Remember, I'm going to be mute most of the time. I will talk about moving to the next question and I will also guide you in terms of the discussions. Most of the things I need you to be able to have those conversations amongst yourselves because you did go through the question paper. And with that being said, let us begin looking at question number one and this is one of those questions where I will edge to have multiple voices not only one person answering the question but as many people because it says in your own words explain the role of research in the field of industrial psychology. So yeah, I expect everyone to be able to give an answer which might not be the same as the next person. So in your own words, how would you describe this? Anyone? I thought it's going to be awkward if you guys don't talk because most of these things or most of these questions you should have gone through them by yourself. Hi, let me give it a try. Yes, you can go. I would say industrial organizational psychology. It mainly focuses on on developing the processes like HR uses it on the processes of how to improve their procedures or processes of firing, training and how they would retain employees. They use it to close the gaps when they do their analysis on on their processes, the the existing processes and they also use it to on their surveys when they want to do the comparison with other organizations and the dynamics of the workplace. They also use it they also use it to to assess the how various departments within their organizations are performing and whether whatever job that they are doing is it giving them satisfaction and how can HR intervene in improving job performance and job satisfaction? Nicely explained, yes. Remember it's also for max. You can keep it to a level of three or four points that you want. You want to also explain the role of research. Don't explain what industrial psychology is, explain the role of research in industrial psychology. So your sentence will need to start the role of research in industrial psychology is two, one, two, three, four, five. Okay, you said it nicely. Anyone who wants to give another perspective in terms of what the role of research is? Research is simply a process of answering questions. In research you collect data or it is a systematic process that involves collecting, analyzing and interpreting information or data and in order to increase our understanding of things that we are interested in or concerned about. If I may stop you right there and go back and say you are giving me a textbook explanation of what the research is. The question was explain the role of research in industrial psychology. That explanation of what research is converted to what will be the main role of research in industrial psychology. I would say maybe the main role is for us to analyze data. What kind of data? Is it to analyze the sales in an FMCG company? You need your explanation in relation to industrial psychology because the question was what is or explain and remember when it says explain it's a vocab that tells me that you need to be able to not only give a definition but also give some explanation and an example of what you are explaining about. Here they want to know what is the role. We know what research is about. Research is about collecting and analyzing data for decision-making. We know that in industrial psychology what will be the role of doing research? Why do we need to do research in industrial psychology? That's what they want you to say. Why do we need to do research in industrial psychology? Okay now I understand. Maybe since we know that it is what it is, in research in industrial, in IOP, it can be used. Supposed you since industrial psychology, organizational psychology, it deals with maybe the employment. You may collect data maybe for a process or for a job that is being advertised to see what kind of a person you need that you need to employ. Then when you have collected that data, everything that's all the qualities, the characteristics that you need for that person, then you can research on the person that you would want to employ. I can also guide you in terms of this question because the question didn't say explain what the research is. If you go to your study guide, I think on page 21, there is research in industrial psychology. If this kind of a question comes up in your exam, when they ask you what explain the role of industrial psychology, use one of those examples. When you explain the role of industrial psychology, why research is needed in industrial psychology? Why would you undertake research in industrial psychology? Use one of those to explain that. Don't put it as a blanket approach in terms of textbook definition because they want to see if you do understand why we do research in industrial psychology. I guess you're all getting an understanding of that. I'm saying sorry, what page? Okay, sorry. I'm looking at, in terms of the number on the, do I have your, let me see. Yeah, I think it's page three on your new study guide. If you use the navigation on the PDF, I think it's page, for me it says page 21. So it's page, number three is a three. Let me go there. Yes, it's three. Thank you. Is it three? Yes, it's three. I speak about the research in industrial psychology. Yes, so but now remember that your paper might not even ask you about the role. You need to also know how to answer the processes of industrial psychology and so forth. So you need to be able to understand all that if they ask you about the processes as well. So but depending on your exam question, but make sure that you know how to explain certain things with definition and then context then an example of what you mean by that. But don't use a general textbook answer when you're doing explanations. You can use them, but you need to also move to the one that the question that they are asking you as well. Okay, so now let's look at question number two. So it means for question one, your answers might be different because everyone will have the way they will understand what the research is and how they will interpret the role of research in industrial psychology and you can pick one of the examples. You don't have to give 10 examples. You just need to pick one. It's the question is for max one for explaining the role, giving it the context and then giving at least one example to show that you understand that role of research in industrial psychology. That will give you for max for doing that. Question two, you're given the survey of resource material for the module and the questionnaire was circulated where students were asked to indicate their preferences and the results are tabulated below. The question here for three marks, so it means every column will be a mark. Number one says complete the frequency distribution table that will include the frequency given. So they have already given you the frequencies. All they ask you is to expand the table. So probably you will have to redraw this table. Some reasons my plans are not working on this documentation. I just want to see if I can guess since I am unable to write on the document, I'm going to have to re-copy it. So you just need to extend the table and have because the question was, let's go back to the question, calculate the cumulative frequencies, percentage frequencies and cumulative percentages. So it means, yeah, you will have your percentage frequencies and you're going to extend your table as well and have cumulative frequencies and you will have the cumulative percentage. So how do you calculate the percentage frequencies? You take your frequency, you divide by total. I hope everybody has answered the question and it will be easier if we have the answers already. Okay, so it's 25 divided by 150. We're starting with cumulative frequency rate. Okay, we can start with cumulative frequency. I can change the values around. Okay, I got from the top going down from tutorial letter 101, I got 25, I'm not sure if I'm right. Yes. And then tutorial letter 201, I got 55. Okay. For tutorial web book 80, for study guide 115, 115. Oh, 115. Yes. And my initial tools 135. And then the last one, the prescribed book is 115. So this will be 25 plus 80 will give you 55, 55 plus 25 will give you 80, 80 plus 25 will give you 115, 115 plus 20 will give you 135, 115 plus 15 gives you 150. Yes. And the next column, you calculated? The next column, the first one, it's 16.7%. I rounded it off, it was 6.66. Is it the frequency, the percentage frequencies? Yes. The percentage frequencies. Oh, the method is 25 divided by 150 multiplied by 100, right? Yes. Yes. Okay, the next one is 20%. Yes, my lads. So 25 divided by 150 multiplied by 100, what did you get? For the 55, I got 20%. For the first one, I haven't written the first column. As kids, the first one is 16.7%. So you rounded it off? Yes. To one. If we rounded it off, then it will be 17%. Oh, okay. Yeah. And then the next one is 20%. Okay, the following. Did you guys wait? Yes. The next one is the same as the first one is 16 or 17%. Then the following one, 23.3 or 23%. Yes. And then the other one is 13%. And then the last one is 10%. When you combine them together, they give you 100%. So I'm guessing that's right. Yes. Okay. And then the cumulative percentage. Okay. This one is 17% the first one. The second one is 36.7, which is 37%. The next one is 53%. And then 76.7. So that's 77%. 77%. And then 90%. And the last one is 100%. Okay. So based on your information that is given here, you need to make sure that you understand what they're asking you to do. If they're asking you, if they give you a hint here and say leave your answers as two decimals, you need to make sure that you leave your answer as two decimals. If they ask you to leave it as an integer, you must leave it as an integer. If they didn't say it is up to you to either leave it as one decimal, two decimal and integer, but make sure that when you round it off or when you are doing the rounding off, you're rounding off correctly. Okay. Because I didn't read through what they asked you to do here. So if they do give you that to say put it as rounding off to two decimals, make sure that your answer is given in two decimals. So this is three marks. So it means every column, irregardless of whether you got most of it right or wrong, every column weighs one mark. So this will be one, one, one, and you will get your three marks. As long as when you complete this table for cumulative frequency, the total at the end where you get to the last row, it's equivalent to the total or the grand total of the number of records you have. And when you do your percentages, the overall total of your percentage should be 100% and in terms of the cumulative percentages, your last row of your records should also be 100% in corresponds to your total cumulative or your total percentages. Okay. So if you don't know how to complete this table, speak now or forever or your piece. I don't have this question paper. I was using the 2020 October November. I don't know how did I miss that? Now I'm so what is happening? I'm not sure. Oh, yeah, I got them lost. I took the one that they posted for us on Wednesday. Oh, okay. I thought we were using the October November 2020. And then your pen, it's not writing. Oh, yeah. He'll be drawing the table next and right, but it's not writing. You just see the red dots with nothing. Are you guys, you leave me like do all these things without saying it? But you can't leave me to continue writing without you seeing what I'm writing. What's wrong with you guys? I was writing because I'm lost. I don't have the question paper. I was writing, yeah. Thanks, man. Sorry. You guys are too well. I'm so sorry. About how many people are here? Hey, hold on. You can't even say anything. And when you raise your hands, I can't see your hands. Because you can't be saying it's been raising your hand, I see there's nothing that's happening. And I wrote on the chat as well. So just mute yourself and talk. Don't wait for me to share. And can you please also make sure that your videos are always off? Okay. Okay, so let's... I won't be able to contribute. Sorry because I made work but I'm listening. Yeah, but make sure that your video is off. Okay, no problem. 10 off your video, yes. Okay, so you guys... Let me see if I can... Because I think there is a permission thing around your document. That is why I cannot. I'm unable to write on it because of the permission. So it doesn't allow me to write on top of it. Just give me a second. Let me see if I can change that. I hope when I do that, it doesn't mess up the paper the way it is. Let's see. Okay, it didn't mess it up. Let me save it. Because I like writing on it so that I can also share back the answers with you on WhatsApp. So let's see. Now I can write on it. I can close there one and keep this one. Okay, so let's start again. Since you guys... You left me like that. So I'm going to start again here and redraw the table again. So you have the values. So you're just going to give me the answers. Since you all have the answers now. So we started with cumulative frequencies. And we said it's 25, 55, 80. Can someone help and call out the numbers? 1, 1, 5. 1, 1, 5. 1, 35. 1, 35. 1, 15. And 1, 15. Then we went on and we did there. Percentage frequencies. And that was? Yes. That is 17%. 20, 17, 23, 13, 13, and 10. And that was 100%. Yes. And then we did the percentage cumulative. And that was? 17, 37, 53. How is it 53? 37 plus 17 should be 50, 54. It's 33.3. Oh, it's because we rounded off that 36.7. And that should be 70. You can do the same thing as you did with the cumulative frequency. You just take 54 at 23. That will give you 77%. Let me see if we did do the same. Yes, we did do the same. It comes up to 77. We do it the wrong way. Yes. And this is 90%. And this is 100. And I've noticed that, yeah, we did it. Sorry. Yeah, we did it actually also wrong because you didn't round it off. Oh, yeah. Yeah. Okay. So that is question number two for three months. Okay. Now we should be able to do everything and we should be on the same path. Now, this question for six months, they are six grams. No, sorry, guys, before we move on. Yeah. No, man, there is something that I always find it difficult to determine around this thing. How do I go about, like, if we're given, like, what is it called, data? So how do I determine the frequency for such data? So for group data, remember, then it means you would have been given, like, numerical information. Yes. And the group or the way you see the study material, that would have been your class intervals. Yes. Yes. So what you do in terms of determining your frequency, you will say how many of the values that were given falls within that group. If it was 10 to 20, how many of the values that you are given falls within 10 and 20. And then you move to the next one. How many falls within that? And so you just make sure that you capture your frequencies relating to the class intervals or the group information. No, let's say, like, let's say, like, it's 10, it's 5 to 20, no? Yeah, on tutorial letter 01. Yes. So what would be my frequency, what would be in that case? That will be your frequency. So let's say for, let me give you an example, a peer example what we're trying to get to. So if I have this data set, which has 1, 2, 4, 8, 11, 13, 15, 20, 31, 33, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. So I have this table, which has my value starts from 0 until 5. Let's say the next one starts from 5 until, because that will be 5, 9, 9, 9, something like that. Remember that when one ends, the other one starts. So from 5 until 10 and 10 until 15, 15 until 20 and so forth and so forth. So now in terms of this information, or maybe let's say 10 until 5, let's change that. Let's change this. Let's change this so that we use up all the bits. So let's say it's from 0 until 10, 10 until 20, 20 until 30, and 30 until 40. So your frequency in terms of this, you're going to say, based on this data set that you were given, remember this is your data. Oh, yes. Based on this data, how many falls within this group falls between 0 and 10? One, two, three, four. Oh, I get it now. How many falls between 10 and 20? That's from 11, yes, 13. Yeah, that's not including 20, because we say it starts from 0 and it's, oh, maybe we can include 10 as well, or we can include 10 depending on how the data looks. So it looks okay. It does not include 0, but it includes 10. In this one, it doesn't include 10, but it includes 20. So it will be one, two, three, four. If we include 20, there are four of them. So you just do that. How many are between 20 and 30? So it means from 21, 22, 23. So you go and count one, two. So there are only two. Two, yes. And that's how you do your frequency for group data. No, no, it's crystal clear. Yes, because with the categorical data, you just group the information in terms of this, because we could have used actually a background to get the count. Yes. No, no, it's clear. Thanks. Thanks. No problem. Moving on to question three. The store manager receives the information about the infection rate of COVID in various regions of the store's globally and blah, blah, blah. Explain what the six graphs mean. So we need to explain this six graph. Use the speedness, ketosis of the graphs to provide a meaningful interpretation. See that? Meaningful interpretation, specifically what each graph means in relation to the infection rate of COVID-19. So yes, you are not going to use the textbook explanation is not going to go well because they don't want that. They want interpretation and they want a meaningful interpretation in relation to the infection. In the textbook, they give you a explanation or a definition of what each one of them are in the study guide. But I expect that you also have a prescribed book that has examples on how you interpret this. So you need to make sure that you know how to interpret each one of them using the same explanation or definition that is in the textbook. So now let's go for it. I will start because I want to show you how you're going to interpret each one of them. Number one, we know that it is normal. What the textbook tells us about normal, it means the mean and the mean are equal. Now, in relation to giving a meaningful interpretation in relation to the infection rate of COVID, I need to say the COVID-19 rates for various regions of the stores globally are symmetrically distributed, which means most of the data from the left and the right are equal or they are balanced. Or I could also say which means the mean and the medium of the COVID-19 infection rate of the stores of the various regions of the stores globally are equal. And that is what they want. Don't go and explain what normal is. Don't give an explanation of saying a normal means the data lines between zero and one and this and that. But they don't want that. They want you to interpret the information in relation to the COVID-19 data that they gave you. So I'm going to repeat. The COVID-19 rates for various regions of the stores globally are symmetrically distributed, which means the data on the left and the right are equal. So it means they are balanced or it means the COVID-19 rates mean and the median of the various regions of the COVID-19 rates of the various regions of the stores globally are equal. And that's how you will explain the graph in relation to the COVID-19 infection rate. So now let's try. Let me see if you guys can explain negatively skewed using the same information that you have in your textbooks. So anyone who wants to try? Anyone who wants to try? I struggled with this one. I failed. I could not. Okay. So now I'm going to also I'm not going to explain all of them to you guys. You need to be able to do that on your own because tomorrow it might not be COVID-19 infection rates. They might do another graph and ask you to interpret it. So remember what the definition of negatively skewed is. It means the tail is to the left, to the left. That's what we know about negatively skewed. How do I then incorporate it with the infection rate? Now, when you interpret it, you will say, I'm not going to repeat the whole sentence again, COVID-19 for the various regions globally, that's your job to do. I'm just going to cut it short. The inflation rate or the infection rate of COVID-19 mean is less than, oh, remember also because the definition says when it's negatively skewed, the mean is less than the median. So I can also say the infection rate of COVID-19 mean, the mean is less than the median. Or I could also say in terms of this information given, the infection rate of COVID-19 data is mostly distributed to the left. The majority of the data is to the left of the distribution. And that's the other way of interpreting negatively skewed. By just following the tail, you can also use that, say the majority of the data is distributed to the left, which means the tail is to the left, which means it is negatively skewed. Or you can use it in relation to the mean and the median and say based on the information given, the mean of the COVID-19 rate infection or rate for the various regions is less than the median of the COVID-19 rate, which makes it negatively skewed. In terms of the ketosis, because the ketosis tells you the risk, it gives you the risk or it also gives you the heaviness of the tail. So whether it's up or down or flat and so forth or peaks up. So for liptochetic ketosis, we can interpret it in terms of that by saying, let me recall my thought because it's ketosis here. And remember that with liptochetic, it means the data is normally, it's mostly normally, it's almost normally distributed. But because we're talking about the peak of the data, it can also highlight that there might be some outliers within the data, that's one, because the peak is too high. Or you can also talk about the data collapsing, maybe having fewer or higher or lower or higher values of infection rates. And that will give you a liptochetic. So you can use that as one of the explanations. One, you can talk about maybe the data having most of the outlier data or having outliers, most likely to have the outliers because the data is most likely also symmetric. Or you can talk about the data being most likely being having lower or higher values at the same time because of the peak of the calf. But you need to talk about it in relation to the COVID-19 rate. So somewhere your explanation is to include the COVID-19 infection rate. Okay, that's one. By modal, by modal would mean that because there are two peaks with by modal. Before we continue, I also struggled with this question, but with liptochetic, I had said there is a greater chance of extremely low or high rate of infection. Yes, that's what I just said. Because with anything that deals with ketosis, it talks about the risk, the high risk. So it might be that there are high risk or low risk of infection. Okay. That is why I said everywhere I spoke about values or numbers, replace that with infection rates. So you need to make sure that your explanation includes infection rates in it. Okay. Yes, your explanation is correct. So in terms of the binomial, anyone who wants to take a step to it, remember there are two modes. There are two peaks. So I would explain this in relation to the COVID-19 infection rates. Can I give you a try? I had said the rate of infection is high in some regions and low in other regions. I'm not sure if I was... Yeah, not necessarily. You need to speak to it in relation to why there are two peaks. Why would you say the two peaks? Could we say the rate of infections is high in some regions due to... Maybe people are not observing the proof code. Now you are explaining something that is not... You're giving reasons why we have two-by-moda. Oh, okay. You need to explain the graph as you see it. Oh, okay. Can I come in? Yes, you can. Before I give you an explanation. Yeah, no, I just want to give a try. If I say it's because the COVID-19 infection rates are fluctuating, would I be wrong? They are fluctuating. It might not be wrong, but what does the two modes tell you? Why do we see two modes and not one mode? What does two peaks mean? If there were more than two peaks, it would mean two or more of them have the highest values, isn't it? All of them have the highest value. Now you only have two peaks. So it means the rate of infection in some areas. There were two highest peaks of rate of infection in two... How do we say this? There were two highest rate of infection of COVID-19 for various regions of the dose globally. Something like that would suffice as an explanation for a by-moda because with by-moda, there are two highest peaks. There are two highest modes. Yeah, so you can talk about them in that sense. To say there were two highest peaks in your data. Infection rates. Think of it as explaining in terms of the COVID weights. Remember the weights? There are two highest intervals with the peak. So when the infection rates were higher than the other types, which is the same as how you will explain this. Okay, does it make sense? Are you getting it? We couldn't hear you properly, Lizzy. There were some echoes in the background. I was saying remember when in South Africa, when they do the briefing on the COVID-19, and we say there is a first wave and a second wave, and this is the same thing. So if this was the first wave and the second wave, what does that mean? It means there were two instances where the COVID-19 rates were high in two instances. That is why there are two peaks. Those were the two most high COVID-19 peaks. But also you could also say the same way as you said it in terms of the low and the high, but that would not give you a clear explanation in terms of why there are two peaks, because then this tells me that there are two instances where there were too high risk, and the rest of the times there were low infection rates. So there is too high, and most of the time there were just low infection rates. Okay, thank you. Okay, now I explain the negative queerness. I want you to explain the positive queerness. How would you explain the graph in relation to the COVID-19 infections? Mine is kind of a lazy answer. It is. The infection rate mean is greater than the median. I'm not sure if we should explain what the median is or if this thing is troubling me. Nope, you don't have to. Okay. Okay, so your COVID-19 rates are mean? The mean is higher, it's greater than the median. Yes, you can also say it like that. Remember it's only six marks, so it will be one mark, one mark, one mark, one mark. You don't have to write a paragraph about it. Just give them a short description of what this means in terms of the COVID-19. The other explanation could be in relation to the tape, you could say most of the data is distributed to the right. Yeah. Most of the COVID-19 rates across all the regions of the stores globally, it's to the right, are distributed to the right. You can say it that way. It will also give you one mark. Okay. And the flat one. Plasticetic, what does that mean? I'm going to assume that because on the left side we said there's a possible high risk of infection rate. Well, here because it's flat, maybe it means it's the small possibility or the possibility is smaller of the infection rates. I don't know. We have a different explanation. There's nobody who wants to try plasticetic. Okay, so in terms of the COVID-19 rates, because it has many high COVID-19 rates and low, and it can also mean they are low COVID-19 rates as well. Possibly there are less risks because also the calf is flat. So your COVID-19 rates might be most likely around the same, I could say, around the same center or the same mean because they are almost similar. They, I'm not sure if you get me. So in terms of the COVID-19 rates, yeah, there are low risks in terms of that. So how would you put it in an explanation? Can I give it a try? Yes, you can. If I say the infection rate is now manageable or under control, like it's not, I don't know how to put it, but like it's now manageable and the risk is no longer that high because now the infection, the virus is under control or it's manageable. That's one way as well. You can also put it that way. Remember, as long as you can speak to the risk level of the information given in terms of that graph, so there is no risk and you can talk about what does flood mean in terms of infection rate. It means they're almost similar pattern. They're like almost constant. So there is no, no store that reports more than the other ones. So the pattern is almost similar. So the risk is almost, yeah. Can I be saying your hand has always been up or is it for now? Oh no, I think I have to switch it off. Is it off now? Okay. Thank you. Okay, so I guess for question three, you have an idea of how to interpret most of these graphs. So don't give, when you do your interpretation, don't give the textbook explanation. Use the textbook explanation to guide in terms of how would you describe the, or how would you explain the graphs, the data that we see in front of you. Okay, so that is six marks. Now let's move on to question four. So question four is measures of relationships. So given the information, I'm going, I'm not going to concentrate more on what is given in the statement. You have read the statement. The relationship between job satisfaction and job performance was zero comma four three, which means your coefficient of correlation is zero comma four three, which is 43%. The mean of job satisfaction, which is your x, which is your predictor variable that we're going to use to predict the outcome. It's 3.1 and the mean of our y, which is our independent, which is our, sorry, which is our dependent, which is our outcome variable, which is the job performance, it's 5.3. X is your independent, which is your predictor variable. Y is your dependent, which is your outcome variable. Okay, so we have the mean of both. The slope, which tells you one additional unit increase or decrease, and this slope is zero comma two nine, which is positive. So it means one additional increase in job satisfaction will lead to an additional increase in job performance. That is the slope. In a way, I'm just giving you explanation of all the values that you see in front of you. Okay, with that being said, what is the difference between correlation and regression? Yeah, you can give your textbook explanation because they're not saying in your own ways or anything like that. You can even go and read what correlation and regression mean and give that statement as your answer. But remember, it is only two marks. So you will get one mark for stating what correlation is and one mark for stating the difference, probably the difference between correlation and regression, which is just giving an explanation of what correlation is that's different to what your regression is. One mark, one mark. Anyone? What is correlation and what is regression? Okay, ma'am, please. Me on correlation, I said it's a measure of the strength of the linear association between two variables. And then on regression, I said it's a way of saying the relationship between two or more variables, of analyzing a relationship between two or more variables. Okay, might be, yes, the others. It can be also the difference between two. One talks about the strength and direction of the relationship between two variables, where one talks about what type of a relationship the two variables as. But in terms of regression, you must think about the influence because regression is about predicting something, predicting an outcome. How X influence the other. So what is the difference between the two? There is a thin line between the two. No, I'm confused. Why are you confused? Is it the way we have to check if the correlation is on the negative or on the positive? But that is the strength and direction. That is what the relationship is about. Yes. And then, so you know what the relationship is about, but what does the regression mean? Because I'm getting confused with this sort of saying analyzing the relationship. Why? Both of them, they analyze the relationship. So but what is the, what makes them both different from one another? I guess I'm stuck now. In correlation is, okay, is, what is it? Correlation is defined as the relationship between two variables, while regression is how those variables affect each other. Yes. I think that's the difference is, yes. It's why and how they affect each other. Yes. Yes. Because we want to know what is the difference between the two. One is a measure that tells you what direction and strength of that relationship looks like, whereas one tells you how each one affects the other. Why X, how does X influence Y? Or how does X affect Y? That's why I said there is a thin line because both of them, they talk about the relationship, whereas one tells you the direction, one direct, it gives you the direction and the strength of that relationship, whereas one just gives you whether the X value or your independent variable, how does it affect your dependent variable? Or how does it relate to the independent variable? So you can either use weights like affect or how does it relate to the other variable? Or you can also use weights like it predicts. One is used to predict what the outcome would be of the other variable. Because they are just asking you there to tell them whether you know the difference between the two. We know both of them gives you the relationship, but do you actually know what kind of a relationship do each of them produces? One produces a measure that tells you the direction and the strength and one tells you whether one affects how one affects the other or how one relates to the other. That's what correlation and regression mean. So find the one that you are able to settle with and use in your explanation of what the difference between the two is. Okay, number 4.3, interpret the correlation coefficient. What does this relationship between job satisfaction and job performance of 0.43 mean interpret that? It's a medium. What do you call it? A medium? Is it medium? Not medium. Moderate. Moderate. So you need to be using two things. Direction. Strength. Interpret correlation of coefficient of 43%. It's positive, moderate, positive. Is it moderate? Is it weak? Yes. Moderate? No, it's moderate. It's moderate. Moderate's positive. Positive. What relationship? Yes. And that's how you interpret. So you will say, you're not going to say just it is moderate positive relationship, it's for two marks, given effort. The relationship between job satisfaction and job performance of 0.43, it is a moderate positive relationship. And that's it. Just like that. So then you can get your two marks. One will be for the strength and the other one will be for the positive. But depending on how cool your lecturers are, even if you write it like this, they can just give you two marks. I don't know how they are worth the marks. Okay, 4.3. What can you deduce about the nature of this relationship between the job satisfaction and job performance? Now, don't tell me it is moderate positive relationship. What can you deduce from this? Think about it. It's a positive and it's moderate. What does it mean in terms of job satisfaction and job performance? That's what they want. It means that the better the job satisfaction, the better the performance score. Thank you very much. That's what you can say. Anyone who wants to try another way, I'm not using beta, you can say. I said the more satisfied people are at work, the higher the performance level. Thank you. You can also say it like that. It will still mean the same thing because as long as it's a positive, it shows an increase and an increase, you can even say the higher the job satisfaction, the higher the job performance. You can say the more people are satisfied, the more the job performance will be on the rise. Things like that. As long as you can show that you understand what does it mean to be a moderate positive relationship or when you have a 0.43%, you will get your one mark. Remember, your answer cannot be the same as the next one, so make sure that you know how to interpret these things in your own ways as well. Okay, so 4.4. Oh, let me write here. High job satisfaction job. Oh, you can say it the same way as you all have been saying it. It means one and the same thing. Or the increase in job satisfaction will lead to an increase in job. You can also use the words like increase. The increase in job satisfaction will lead to an increase in job performance. You can say better job satisfaction will lead to a better. You can use those weights as long as it shows that there is a positive relationship between the two. It's just one mark as well. Okay. 4.4. Calculate the percentage of the common variance. Remember your common variance is your R-squat. And your relationship, this is your R, so which makes your R-squat is just 0,43-squat. And do the calculations. 0.18. Now, you need to show the calculation as well because I think you will get a mark for showing calculation and getting the answer. But you also will get a mark for showing the diagram. Do you still remember how to draw the diagram for showing the common variance? So you have your job satisfaction and so you're going to write your job satisfaction and job performance. And there is in the between, this is where your 0,18 will be. You can write it that way. And 0,18, you can write it as 0,18 or you can write it as a percentage depending on how you want to represent it. You can leave it as a decimal or you can multiply the decimal by 100 and write it as, or you can say it is 18%. It's up to you how you represent it, but that will give you two marks for doing that. Okay. Okay. So that will be 4.4. Let's go to 4.5. Now with 4.5 it says, you wish to predict the employee's job performance score. Now we need to determine what the new value of the, or the outcome, which is the job performance is. 4.5 says, which of the two variable is the predictor variable? You have two variables, job satisfaction and job performance. Which one is the predictor variable? I think it's the job satisfaction, which is the independent variable. Your independent variable, you don't have to write independent variable. I'm just saying independent variable, which is job satisfaction. That is the predictor variable. For one mark, you just write the job satisfaction. Differentiate 4.6, differentiate between the slope of the line and the y-intercept. Differentiate for two marks. What does the slope mean and what does the y-intercept mean? That way you should be able to differentiate between the two. The slope tells you the change in the values of your regression line in relation to your dependent and independent whereas your y-intercept tells you that it is the average value when your independent variable is equals to zero. But use your own words, differentiate between the slope and your y-intercept in relation to how you know your answers. So what does the slope mean and what does your y-intercept mean? You can also say in relation, the changes in y, in x. In state of saying x and y, remember you can say independent and dependent. So this y, you can replace it by dependent and this x, you can replace it by independent. And your y-intercept, it is the average when your independent variable is zero. All we can say is the estimated value or the estimated average, which is the same thing. The estimated, you can use average or you can use the estimated value or average, the estimated values of y of your dependent. That's why they invented computers. This thing of writing always is not working well for us. We are used to using, to typing. The estimated values of the dependent, the estimated value of the dependent value when they're not your, because it's not about you, it's about the data when they, come on, when the independent variable is zero, or you can say the estimated value of your dependent variable when the independent variable is zero. So you can use that or you can go and look up the definition in terms of your textbook. What does that mean? How do they describe your y-intercept in the slope? But that will also surface. That's the difference between the two. One is the change in the values of x and y and the other one is your estimated value of y when x is zero. Let's do the last one and then we take about 10 minutes break and then we'll come back for part two and see how far we can get with the other questions. So any question, any comment in terms of 4.6? You can look up the definition actually in your textbook if you want. If you don't feel comfortable just writing it the way I wrote it, you can use the one that is in your study guide or your textbook. Explain what the slope is and your y-intercept is because that will give you the difference between the two. And then the last, how many? We still have 4.8 and 4.9. 4.7. Calculate the y-intercept. So this is your job to do. Your y-intercept which is b1, b which is b0. So which one do you use? I'm not sure which formula you use now. I need to go back to the, do you use y is equals to b0 plus b1x or do you use y is equals to a plus bx a plus b b1x? Is that the formula that we use? You use or we use y is equals to mx plus c or whichever one that you are using. So if you're using the a and the b, I need to be able to say in terms, this is the regression line. Remember that's what I'm asking you in terms of the regression line. If these are the formulas for the regression line, therefore the intercept you can use e and that is the other thing that I am not sure. So the intercept is a if you're using the second one. Sorry, the y is d times bx plus a. Yeah. So the intercept that is a, which will be your mean for y minus bx, the mean for x. So because they gave you the slope, let's go back there. The slope is b. So you just take your slope, the mean of x they gave you, that is the mean of x, which is your x bar, the mean of y, which is your y bar. You just substitute them into this formula. Okay. So this is the formula that you use. So I got 4.41. Let's make this smaller so I can substitute the values. Okay. 5.3. 5.3 minus b of 0 comma 2 times the mean of x, which is 3.1. Yes. And what do you get? 4.41. Let me just confirm. Yes. 4.4. I don't know why I said 1. And that is your intercept. So if we know what the intercept is, remember what we said what the intercept is. It is your mean average or your average value of your independent variable when your x variable is equals to 0. Remember that. So you need to take into consideration that value later on. 4.4. Yes. The next question is asking you, calculate the job performance of an employee with the job satisfaction of 8. So we're going to use this formula that we identified there to answer this question. So you're going to say y hat is equals to, we said bx plus 8. That's what you told me now. Yes, that's it. Just substitute the value of b is 0 comma 9. The value of x, they give you the value of x. This is your x, x is equals to 8. So we've seen x, we just replace it with 8 plus the value of 8 is 4.4. And calculate that. 6.72. Until you get it, 6.72. And that is your new estimated value of y when x is 8. The last statement says, give a graphical representation of the regression line by indicating the intersect, which is this value that we calculated, 4.4. The predicted value of the worker of 8, which is that value on the regression line. So now all you need to do is draw the regression line like this. Because it's five marks, you need to pay attention to detail as well. And look at the marks. Because it's five marks, you get five marks for also making sure that you label your graph correctly. So yeah, you can label your graph as job satisfaction. So job satisfaction, which is your, you can say x is equals to job satisfaction. And yeah, you can say y is equals to job performance. And you need to also have a title for your, this is the regression line of job satisfaction and job performance. You can say like that. The regression line of, which is your title, regression line of job performance and, sorry, job satisfaction and job performance. Okay. So the other thing you need to remember is indicate your y-intercepts. So we need to indicate our y-intercept of 4.4. So let's select that value there. We can just say that value there is 4.4. Therefore, it means our graph will pass through at that point. Remember, at this point, x is zero. So at this point, x is zero because, yeah, at the end there, x is zero. So it means our graph should pass some way there. And also remember that your slope is positive. Why is my slope positive? Well, how do I know that my slope is positive? That is that. And because also my correlation coefficient tells me that it's positive, so therefore it means the line that I need to draw should go up like this. Remember, because of the positive slope and the positive regression line. So my line is going to go up. But now we need to also remember that we need to also represent the value of 8. So y is 8. Let's say 1, 2, 3, 4, 5, 6, 7, 8. Let's say this point there is 8. And we did estimate what the outcome is, which is the y value of 8. So your graph will look nicer than my one. So I'm going to reduce the line a little bit so that I can have this dotted line there and this dotted line there. So that at this point, I can have a point there that says 6. At this line, it's 6.72, which is the new y value that I estimated. I am so sorry because now my graph is so small. My graph is so small and everything is overlapping. But I hope you get an idea of what I am trying to get to. 6.72, which is the y value that we estimated where x is 8, y is 0.27. And then what you just need to do is dot, dot, dot, dot, dot. And you can also do the dot, dot, dot, dot there just to demonstrate that those are linked and the dot, dot, dot, dot, dot. And there for 5 marks. So possibly you get a mark for labeling your graph correctly, for labeling your title, and for drawing. So you will see where the 5 marks will go from. I am going to stop the recording now. I'm going to give you 10 minutes. Let's take 10 minutes break. Let's meet again at Korapastry. Let's come back at Korapastry. I'm going to stop the recording so that we can have part 1 and part 2 of the recording as well.