 In this week, we saw about descriptive analytics. I started about what is the data and how to describe the data in plots or graphs. We discussed very basic plots and which plot to choose. Let us look at few examples about descriptive analytics. That is, let us start with Google Analytics. If you have a website and if you have a website you can add Google Analytics code on it and you can see how many students are, how many US are using this website, what are their behavior and everything. Let us check the Google Analytics and understand what this analytics means here. So, this is a sample Google Analytics page of our website, one of our website. Here I am showing a data of last 28 days from the Google Analytics. So, it is simple, it uses a simple line plot. So, you can see the line plot and it tells you that one particular day there are more number of users compared to the other days and how this user is changing over time. So, the number of users is really low except the one particular day there are more number of users on the particular site and it is again low. So, last 28 days, this shows the simple line chart. Why line chart? Because it is shown to show the progress or trend over time, over time that is from last 28 days. So, it is a simple chart to show how many users are visiting our website. Or if you look at the user traffic, Google Analytics gives me the bar chart, a stack bar chart. So, here the bar chart is showing last 90 days, not 28 days, it is more. And you see there are more number of users or direct users like they did not search to go to Google and find it instead. We might have shared the link to them, they would have clicked the link directly in their mobile phone or a WhatsApp or Facebook page or from the website of our web page. So, there are like most number of users, I would say like if you compare all the users, around 90% or more than 90% of users are direct links. There are few users are from social link and few from organic search. Organic search is the one who came to this website by searching in Google. So, it is not happening much. If you are a website owner, if you want to know why the people are not coming to your site from Google search, it might be because you might be lagging the tag words or keywords or you have not done the SEO like a search engine optimization. SEO will get more kind of customers from Google search to your web page. But this web page is not doing good in terms of pulling the users from Google search. So, most of the users are from direct link. So, let us look at this plot. We have not talked about this plot in our basic plots. This one is called 8MAP, this is a space plot. So, space plot is very easy to understand because it is to show the whole map or map in that which particular place is more concentrated. It is also kind of a heat map on the space. So, here the more darker indicates a lot of users from it. So, maybe around 95% of users are from India, very few are from Ethiopia or Mauritius or Tanzania or United States, a few users from Japan elsewhere. So, there are very, very few users are from other continent or other countries, but most of users from India thus indicates in the space chart. This is 8MAP, we are looking at 8MAP on last 30 days. So, if you look at the heat map, it is distributed for 7 days on all the time like 24 hours and 7 days. So, this darker color indicates the more number of users are using that particular time, the light color indicates the less number of users are using this particular or checking this site. You can understand that from morning to am to 4 am, this is almost very less users have gray color, which indicates there is no user, this gray color box indicates there is no users using this space at that time. It is obvious that most of these users are from India. And so, obviously they will be sleeping at 2 to 4 pm, they are not checking any websites or they are not looking at the websites for our websites. So, that is obvious. And if you look at it for the Thursday on an average of 30 days, Thursday around 10 am to 2 pm as a more number of users seeing it, we do not know what happened. If you remember the first chart I showed on particular day, there are more number of users that particular day might be to a Thursday, that is why this number is increasing. So, you have to compare not just one chart, we will tell you all the detail, you have to combine this chart with the number of the day which the students had more number of users, we will tell you that the time 2 to 4 because the sleeping time for most of users in India, that is why it says that. And this is a behavior flow. This is a bit advanced to know that which particular page, particular page a student moved from the landing page to other page. Almost all the user landed on this page, that is the home page, which means they directly came here, they did not come via some other page. So, they directly come to our page. So, that is why we saw that direct search is directly to this mode 95% after they land on the home page, some of them dropped, most of them into the technology online technology page or second page, few of them into some teaching links or something like that. So, you can know that where the user wants to go from one page to other page. So, if your website and if you have a Google Analytics code can be embedded with that and you can check your analytics in your Google Analytics. This is Google Analytics of one of our web page which we embedded recently, then we are looking at this data. Like it is good that all the people who land most 24 are going to this particular page, 14 are going here and say almost 50% are going to the next page, almost 50% might be dropping out or people might be landing from different pages directly instead of the landing page. So, you can see this interaction, first interaction, second is you can go further, but if the drop is increasing, there is no need to go further. This kind of behavior flow chart actually tells you within the web page where the user is going from one page to other page. So, this is useful for viewing the page. Consider you are creating a learning environment which has 10 pages of reading and they have to create something, they have to answer something. You expect the students to read 10 pages of document or some content and ask them to answer some questions, the simple learning environment you are creating. In that, if you have the analytics like this, then you will know that when the student transfer from one particular page to other page, what happened, where they are dropping out, all this information can be captured by using this kind of behavior flow. So, we saw one example that is Google Analytics dashboard. We will have, we will see couple of more examples in a descriptive analytics like a dashboard from YouTube analytics or a dashboard from some other MOOCs or something like that. Thank you.