 Hello and welcome to the session. In this session we will describe association between two variables using scatter plots. And we can say here we will describe association in a binary data using scatter plots. Now a binary data involves two variables say X and Y. And now we will see association between these two variables that is between X and Y. Now let us see what is a scatter plot. Now a scatter plot is a graph that shows a relationship between two data sets. And these two data sets are graphed as order pair in the coordinate plane. Now let us see one example. Here we have data of the two variables X and Y. Now we can plot them as the order pair X, Y in the coordinate plane. First of all let us plot the ordered pair 4, 10 on the graph. Now here this is the plot the other points also which we have plotted a scatter plot. Let us discuss association between two variables that are related. Relationship we construct and observe a scatter plot of points plotted on a set of error plots. The independent variable is placed on the horizontal axis and dependent variable is placed on the vertical axis. Now there are three types of relationships. First is positive relationship is negative relationship and third is no relationship. Now for positive relationship we look at the pattern of scatter plot. If it is moving upwards then there is a positive relationship between two variables X and Y. It exists when dependent variable Y increases the increase in independent variable X. Now the relationship between weight and height in this scatter plot. Here weight depends on height. When height increases weight also increases. Here you can see the pattern of dots they are moving upwards. So there is a positive association between height and weight. Now let us see negative relationship. For this again we look at the pattern of scatter plot. If it is moving downwards then there is a negative relationship between two variables X and Y and this exists when dependent variable Y decreases increase the relationship between students per computer and years. Now here you can see with each passing year number of computers increased. So the number of students using one computer decreased. Now in the year 1987 there were 35 students per computer and in the year 1999 it was reduced to 5. So here the graph is moving downwards. So there is a negative relationship. Look at this pattern of scatter plot. Now this pattern is neither moving upwards nor downwards but the points are placed randomly on the plane. We can see here exists no relationship between the two variables X and Y. There is no association between the two variables. Let us see the relationship between intelligence quotient that is IQ and weight of students. Now from this scatter plot you can see that there is no association between IQ and weight of students or you can say that there is no relationship between IQ and weight of students. At the plot the dots are scattered all over the graph which means there is no relationship between the two variables. So this type of scatter plot means that there is no association between the two variables. And now let us discuss degree of association. Now we look at this pattern of points to make judgment about the strength of relationship. Now by degree of relationship we mean strength of relationship. Now the strength can be strong, moderate, weak and zero. The following scatter plots now when degree of association is strong then the dots on the scattered plot are very close to each other. Now in figure one you can see that the dots on the scattered plot are very close to each other also here the points are moving upwards which show positive relationship between X and Y. So as the dots are very close to each other and they are moving upwards so here the degree of relationship is strong and this relationship is a strong positive relationship. Now in the second figure you can see the points are neither close nor too far so here the degree of association is moderate also the points are moving upwards a moderate positive relationship. Now let us see the third scattered plot. Now when degree of association is weak then the dots are far away from each other so here the points are moving upwards but they are very far away from each other so it is a weak positive relationship. And when we have zero strength that is when degree of association is zero then it means there is no relationship between two variables. Now here in the fourth scattered plot the points are scattered all over which means there is no relationship between the two variables so here degree of association is if we have relationship moderate negative relationship and weak negative relationship. So in this session we have described association between two variables using scattered plots and this completes our session. Hope you all have enjoyed the session.