 Hello students, we are going to cover the next module which is module number 14 of our data size course. Ismaham, we are going to cover statistical variables which is very very important rather this is the essence of the statistics, what variables we are, variables are basically your numbers which we are going to, the data, we cover or represent our data in terms of variable in statistics. It is basically a data item which has different classes, how you represent it, it is qualitative, it is quantitative, then there is something else in it which is a classification, I will share a whole diagram with you, so you will understand better. As you can see that there are two types of variables, qualitative and quantitative. Quantitative variables are your numbers basically, as we have discussed data types in the beginning, blood group, blood pressure, speed, these are all our things, these are numerical variables where there are quantitative variables and the qualitative variables are attributes, basically as we have discussed, race, color, if the name of the blood group is qualitative, its value is quantity, its measure, but its name is if the blood group is A and B and male, female, these are all its attributes. Whether it is something or not or how it is, these are your qualitative variables, there are further classification as you can see, continuous variables, discrete variables, they are nominal and your cardinal, so in different ways, the different types of data available around us are basically our different types of variables. So quantitative variables, as I said, those things which we can count in terms of numbers, what is its quantity of anything, like the individual's height, weight, population, in a city, these are all our quantitative variables. Then there are discrete and continuous, discrete variables, like the number of persons, it can be 1 or 2, 1.2 or 1.5, so these are our discrete variables. And your continuous variables, like the blood pressure, it is basically a continuous number. You will now understand what is the difference between discrete and continuous, basically and how we can interpret them, how we can use them. Qualitative variables, as I said, these are attributes, they are basically about different things which we talked about, about your gender, your colour, your nationality, such things which are qualitative, like I said, these are attributes of something. For example, the number of trees, plants, trees, flowers, these are all attributes of different things. When we count them, the number of flowers becomes its numeric value. But in itself, it is a discrete variable. Ordinal variables are basically which come in order, like if we look at age group or height group, these are the things which come in order and they are like this, this is the highest, this is the medium, this is the low, this is the elder, this is the middle, this is the younger. These are basically your ordinal values. These are naturally things which come in order, and in this way, you calculate them, use them, and evaluate them in your analysis. These are used in a lot of surveys, like we are giving an example of customer satisfaction surveys, they ask if the customer is very satisfied, dissatisfied, the average is his satisfaction level. In this way, you collect multiple surveys like this. Similarly, frequency, this is another example. In nominal variables, it is like gender, race, eye color, all these things. But these things are not totally independent. If you have one qualitative variable, we count its quantity as well, when we count its occurrences, then we provide analysis of both things together, but this is just a way of identifying different variables. This chart, this is very interesting, you should understand everything from one chart, because what I was talking about, if a person has a numerical variable, then how many children do they have? How many children do they have? Where do they live? If they live in Pakistan, then they are qualitative, but if they exist, then they are numerical. In this way, your different variables are linked with each other, they are not totally exclusive. Because if we talk about statistical data, then we have to see that if this thing is qualitative, how many occurrences it has, how many deaths it has, how to use it, whether it is a house, whether it is a business, whether it is a business man, whether it is income, whether it is tax, then these are different attributes that are only related to business. Similarly, if there is a farm, if we talk about dairy farms, how many buffaloes, cows, goats, how much milk they give, how much milk they eat, then these are different variables that are related to your entity or farm. Similarly, your occupation is that you are a producer, you are a teacher, you are a professor, you are a doctor, this is your one attribute, your qualitative data. Then how much is your income, how much tax you pay, how many patients you see in a day, whether it is quantitative or continuous, your discrete, all these measures are linked with one entity. Basically, I want to tell you through this slide, because one entity which can be a person, it can be a business, it can be a government organization, or it can be a farm, it can be a public or private business. With that, all kinds of data are associated with it, which basically represents it, in this case, we perform different types of statistics, then we conclude different results.