3. Plotting Points [7 Marks] [a] On the graph below, width, w, is the explanatory variable that is plotted on the X ads [the horizontal), and length, L, is the response variable that is plotted on the Y axis [the vertical). Reading from Table 1, plot Samples Numbers 1, 13 and 25 as points on the graph, and label each with its Sample Number. Scatterplot of Length of Ivy leaf versus its width. L 120 100 80 Length of Leaf (mm) 60 40 20 20 40 60 80 100 120 W Width of Leaf (mm) The actual scatterplot, with all 25 of the Samples accurately plotted, is presented below. You should clearly see that the diagonal line drawn on this scatterplot is not the line of best fitfor the sample points. (b) Use a ruler to draw in your line of best fit for all the data points, below, and label it as "line of best fit"- [21 Scatterplot of Length of lvy leaf versus its width. L 120 100 80 Length of Leaf (mm) 60 40 20 20 40 60 100 120 W Width of Leaf (mm)For the sampled data points, the association between length and width variables is evidently 121 linear. What is the direction of the association? What is the strength of the assodation? A. Prediction. [7 Marks] Based on the line of best fit in the graph above, a linear equation can be derived and used for predicting either the length (2) or the width two of any leaf from the same ivy plant. Assume that the equation is L = 1.52 w - 24.7 Based on this equation for the line of best fit, any 1 mm increase in leaf width corresponds to 11] what increase in leaf Length? Use the equation to predict, to the nearest mm, the Length of a leaf whose width is 120 mm. 131 State whether this prediction is reasonable and explain your reasoning Use the equation to predict, to the nearest mm, the width of a leaf whose Length is 77 mmm. 131 State whether this prediction is reasonable and explain your reasoning