The graph displays a residual plot that was constructed after running a least-squares regression on a set of bivariate numerical data \[(x,y)\]. A residual plot has horizontal axis, x, which ranges from 0 to 10, in increments of 1. The vertical axis is labeled, residual, and ranges from negative 0.5 to 0.5, in increments of 0.5. 10 points are plotted as follows: (1, negative 0.9), (2, negative 0.2), (3, negative 0.3), (4, 0.5), (5, 0.3), (6, 0.2), (7, negative 0.1), (8, negative 0.4), (9, negative 0.7), and (10, negative 0.9). All values estimated. \[\small{2}\] \[\small{4}\] \[\small{6}\] \[\small{8}\] \[\small{10}\] \[\small{0.5}\] \[\small{\llap{-}0.5}\] \[x\] \[\text{\% Decomposition}\] What can you conclude from this graph? Choose 1 answer: Choose 1 answer: (Choice A) There appears to be a linear relationship between \[x\] and \[y\]. A There appears to be a linear relationship between \[x\] and \[y\]. (Choice B) There does not appear to be a linear relationship between \[x\] and \[y\]. B There does not appear to be a linear relationship between \[x\] and \[y\]