 Hello and welcome to the session. In this session, we will learn to construct Vax and Viscouplates. Now we know that media writes the data set in two equal parts and profiles divides the data set in four equal parts. A Vax and Viscouplates is a diagram that is constructed using the median, the profiles and extreme values. And here a Vax is drawn around the profile values and the Viscous extend from each profile to the extreme values. And here the median is marked with a vertical line inside this box. Now when you can see, a number line is drawn for the given data. In this diagram, the Vax starts from the profile which is 38 to the upper profile which is and the Viscous starts from the upper profile extend to the lower extreme value which is 23 and the other Viscous extend to the upper extreme value which is and the median is 39 which is shown by the vertical line inside this box and this horizontal line inside the box shows the interquartile range. In a Vax and Viscouplates, we should know these five values that is the lower extreme value, the upper extreme value, the lower profile, upper profile and the median. From these five values, we can easily construct a Vax and Viscouplates. Also, a Vax and Viscouplates separates data into four parts even though the parts may differ in length each contain 25% of the data. Now let us discuss this example in which we have to construct a Vax and Viscouplates showing 10 pictures of various cities and here this data is given to us. Now in the first step, we will arrange the given data from these to the greatest and arrange it we get 15, 22, 22, 26, 27, 29, 30, 31, 32, 36 and 36. Now in the second step, we will draw a number line that covers the range of data. Now in the next step, we will find median, extreme, upper and lower profile values. Now for the given data, the number of times N is 11 which is N. So the median will be the median value and where the median Q is equal to the median value. Now where the median value is 29, so median is equal to 29. Now we know that median of lower half of data set that is the values below the median value is all the lower quartile and the median half of data set is called the upper quartile. Here you can see that the number of times in the lower half of data set is 5 which is odd. It means the median of these 5 values will be the median value. So the lower quartile Q1 is equal to 22 and similarly we can find the upper quartile also. So from the given data, upper quartile Q2 is equal to 32 and from the given data, the lower extreme value is 15 and the upper extreme value is 36. Now let us plot these 5 values on the number line. We have plotted these 5 values on the number line where Q is the median, Q1 is the lower quartile and 36 are the lower extreme, the upper extreme value respectively. Then in the next step we will draw the box so that it includes the quartile values. That is we will start the box from Q1. Here the vertical line inside the box shows the median Q to the extreme data points. In this way we have completed the construction of box and risco plot for the given data. Risco plot is way helpful in interpretation. This diagram tells us about the spread of data to our box is short. Then the values of the data once is written and this long of the data. In that part we can interpret the data for this example. Now here the lower quartile whisker that is this whisker is longer. In that of the upper quartile whisker so the values are more spread out below the lower quartile than above the upper quartile. Now let us discuss double box and whisker plot. Now this is used to compare two data sets. A double box and whisker plot consists of two box and whisker plots draft on the same number line. Now let us discuss this example in which we have to compare the support prices of shop A and shop B. Now we are from the number line we can see that the extreme values for shop A are 250 and the extreme values for shop B are 300 and 900. So the range of prices for shop A is equal to the greatest value which is 600 minus the lowest value which is 250. So this is equal to 350. Similarly we can find the range of prices for shop B which is equal to 900 minus 300 600. So the prices vary no in shop B when in shop the effect of outlier is a value that is much greater or much less than all other values in the data set. Now consider an example for this. In this the data is given to us as 20, 22, 30, 32, 35, 30, 44, 38 and 90. Now here we can see that L are between 20 and 38 that 90 is very far away from all other entries. So we call it as an outlier. Now while plotting box and whisker plots we have to check for outliers greatest value that is not an outlier and leave the outlier value. So this is the box and whisker plot for the given data in which the whisker with other quartile is till 90 but with the next greatest value of the data that is 48 which is not an outlier and we will use it on the number line. So in this session we have learnt to construct box and whisker plots and this completes our session. Hope you all have enjoyed the session.