Speaker 1: Hi everybody, I am Naufal. Welcome to my channel. Today, we are going to discuss regarding a very interesting topic that is data analysis. Analysis of the data and the steps of data analysis in quantitative study. So, what is meant by data analysis? In research, you are collecting the data using different methods, that is through interview or through observation or through questionnaire, you are collecting the data. For example, a teacher wants to collect the data from the students. So, she is conducting an exam. So, to conduct the exam, a question paper is required. So, that questionnaire is used. Using that questionnaire, using that question paper, the teacher is conducting the exam. So, teacher is getting the answers. So, that answer sheet is the data. The answer sheet is the data. So, to analyze the data, after collecting the data in research, you have to analyze the data. So, what is meant by analysis? Analysis means you are examining that data or you are evaluating that answer sheet. So, analysis means evaluating or examining in detail, in depth. In detail, you are examining or in detail, you are evaluating the data. The data is that answer sheet. I am just giving the example only. So, we can see the definition of data analysis. So, what is meant by data analysis? Data analysis is the process of breaking complex topic to a smaller part to gain better understanding of it. So, data analysis is a process of breaking a complex topic, that is, that answer sheet to a smaller part, that is, putting marks. So, data analysis means you are breaking a big topic to a small one. For what? To gain better understanding of it. Data analysis is the process of breaking a complex topic to a smaller part, to gain better understanding of it. So, all the collected answer sheet, that is the complex topic, you have put the mark. So, you have break into smaller parts. For what? To gain better understanding. Now, the teacher has got a better understanding regarding that answer sheet, that is, data analysis. Next, we can see the steps of data analysis in quantitative study. The steps of data analysis in quantitative study, mainly you can see four steps. First one is data preparation. Second one is describing the data. Third one is drawing the inference of data and fourth one is interpretation of the data. First one is data preparation. Data preparation means you are checking and cleaning the data. You got an idea regarding what is data and what is analysis of data. So, the steps of data analysis, first one is data preparation. You are preparing the data. In preparation of the data, you are checking and cleaning the data. You have to keep it in mind. In this step, you are checking as well as you are cleaning the data. It includes five sub steps. So, you will get a better idea. It includes five sub steps. First one is compilation. So, what is mean by compilation? Compilation means bringing together all the collected data. So, bringing together all the answer sheet collected by the teacher and arranging in a particular order according to the serial number or according to the roll number of the students. That is compilation. The first step is compilation. That means bringing together all the collected data and arranging in a particular order. That is you are bringing all the collected answer sheet together as well as arranging it in a particular order. That is according to the serial number or according to the roll number. That is compilation. Next step is editing. After compilation, you are doing editing. So, what is mean by editing? Editing means you are checking. It is a process in that you are checking the completeness, utility as well as the accuracy of the answer. The researcher is checking regarding the completeness and the accuracy of the answer. That means all the answers, all the questions are answered properly or not. Any question has skipped or not is checked in this step. In editing, the researcher is checking all the questions in the question paper is answered or not. Is there any question is skipped? So, that is editing. Checking the completeness as well as the accuracy of the answer is called editing. Next one is coding. So, what is mean by coding? Coding means transforming the statement into a symbol. That means suppose a statement and making that statement to a symbol. It may be in number or it may be in alphabet. Suppose for example, in your study, in your data for male, you are giving a code that is 1. For male, you are giving a code 1. So, you are using a numerical code. For male, you are giving a code that is 1. For female, you are giving the code 2. That is coding transforming the statement to a symbol. The symbol may be alphabet or number. It may be 1, 2 like that in number or in a, b, c like that in alphabet also. Always keep it in mind. For one character only, you should give one code. If you use number 1 for male, you cannot use that number 1 to any other statement. So, you are making a symbol for a statement. That is coding. Next one is classification. After coding, you have to classify the data. In some research, so much data will be there. So, it should be classified according to the groups as well as according to the particular classes having same characters. For example, male as well as female, you are classifying that data. According to the group or according to the class level, you are arranging the data. You are classifying the data. Those having common characters, having particular mark range from 50 to 60, you are classifying that data in an order. Like that for male and female, I am just giving the example only. So, classification means you are classifying the data in particular classes or in particular group. Those who are having common characters, that is classification. Next one is tabulation. After classification, it is tabulation. So, what is meant by tabulation? Tabulation means recording the classified data in mathematical terms. You are recording the classified data in mathematical terms. In symbol, you can call it as tables. In symbol, you can call it as tables that is in rows as well as in columns you can make. For example, I am just giving. This is tabulation. Here, you can write male, female, their number of male and as well as number of females, their marks like that, tables you are making. That is tabulation. Tabulation means recording the classified data in mathematical terms that is using tables that is rows as well as in columns. In rows as well as in columns, you are writing regarding the classified data. How many males are there? How many females are there? Like that in a column and in row, you will write it. That is tabulation. I am giving the example only that is tabulation. That is regarding data preparation. Next one is describing the data. The second step of data analysis is describing the data or descriptive statistics. In statistics, you learn in detail regarding what is descriptive statistics. So, here that is describing the data or descriptive statistics means the researcher. In this step, the researcher will describe the basic features of the data and the researcher will summarize a simple summary. The researcher will make a simple summary regarding the data as well as the researcher will give or the researcher will describe a regarding the basic features of the data. For example, regarding the percentage of mark and regarding the average mark of the students in a particular class that is mean, median, mode, range and standard deviation that in statistics you will learn in detail. So, describing the data means describing the basic features of the data as well as simply summarizing the data. In a simple manner, the researcher will summarize the data regarding the percentage of the mark, regarding the average mark of the students and all. So, regarding that, regarding descriptive statistics, you learn in detail in statistics. Now, you have to keep it in mind regarding this much point only for data analysis. Next one is drawing the inference of data. Drawing the inference of the data or inferential statistics, it is also the part of the statistics only. That is drawing the inference of the data which means making the conclusion or the judgment of the data. Making the judgment or the conclusion of the data. For example, you want to know regarding the relationship between the two things or the association between the two things or the difference between the two things. For example, you want to know regarding the mark range or mark average between the male as well as the female students as well as height and weight of the students. So, in that, the inferential statistics is used to know the relationship between the things, to know the association between the things and to know the difference between the things. Here, you have to keep it in mind to draw or to make a conclusion and to make a judgment is occurred in this step. So, drawing inference means making a conclusion and judgment and it will help to identify regarding the association, regarding the relationship and regarding the difference between the things. Mainly t-test as well as ANOVA and all are used in inferential statistics. That is inferential statistics, you will learn in detail in statistics. The last step is interpretation of the data. So, what is meant by interpretation of the data? Interpretation of the data means if you got the result, after analysis you got the result. In interpretation of the data, you will do the critical examination. You will do the deep examination regarding that result and you will explain the result. You will explain the result. Explaining the result as well as making that result in an understandable manner, making the sense of the result is called interpretation of the data. So, in analysis of data, you got the result and finally, in that result, in interpretation of data, what you are doing? You are doing a critical examination. Deeply you are examining that result and you are making an explanation regarding that result and you are making a sense of that answer that is in an understandable manner. For example, in the mark sheet regarding different subjects, regarding different subjects, the marks of the students. For example, in anatomy for theory, how much mark that student got and regarding the practical and regarding the internal assessment and the total mark like that in a proper order, it is used to show the result that is interpretation. Critically examining the result, making explanation of the result and making a sense or in an understandable manner, it is explained that is interpretation of the data. That is all regarding the steps of data analysis. We will meet soon with another video. Till then, thank you and goodbye.