 Hello and welcome to the session. In this session we are going to discuss the following question and the question says that the given box plots show the maximum temperature in degrees Fahrenheit recorded by the weather stations for two cities A and B. Study the box plot carefully and compare the two distributions. Now let us start with the solution of this question. When comparing two data sets one should discuss each characteristic of the data that is center, spread, shape and outliers and here we are given the maximum temperatures of two cities in degrees Fahrenheit. In order to compare the two data sets of cities we will discuss center, spread, shape and outliers of the two distributions. So first we will discuss center for the two distributions. We are given box plot so we can say the measure of center will be median. The vertical line inside the box is drawn at median so we see that median for city A is given by 40 and for city B it is equal to 31 so we can say that average temperature of city A is greater than average temperature of city B. Here we have seen that the average temperature of city A is 40 degrees Fahrenheit and for city B is 31 degrees Fahrenheit so we can say that average temperature of city A is greater than average temperature of city B. Now we are going to discuss shape of the two distributions. Now here we will see whether the two distributions are symmetric or skewed and in box plot we see length of the whiskers and position of median to take symmetry and skewness. In city A we see that the median is exactly at the center of the box and length of the whiskers is also same so we say that the shape of the distribution for city A is symmetric and for city B the right whisker is longer than the left whisker so we can say that the shape of the distribution is skewed to the right. Thus we say that the shape of the distribution for city A is symmetric and for city B is rightly skewed. Now we shall discuss spread for the two distributions. We know that the spread of the distribution refers to the variability of data. If the data cluster around the central value then the spread is smaller the further the observations fall from the center the greater the variability or spread of the data and here we can see values for city B are widely spread then the data set for city A and lastly we are going to discuss outliers. We know that an outlier is an observation that is numerically distant from the rest of the data since there are no outlying values in the two distributions we say that there are no outliers so in this session we have compared the two distributions in terms of center, shape of the distribution, spread and outliers. This completes our session. Hope you enjoyed this session.