# data[].attributes.headline
Which answer is the best estimate of the residual value when x = 1?

# data[].attributes.subject
Which answer is the best estimate of the residual value when x = 1?

# data[].attributes.body
1.5

# data[].attributes.headline
The residual plot for a data set is shown.Based on the residual plot, which statement best explains whether the regression line is a good model for the data set and why?

# data[].attributes.subject
The residual plot for a data set is shown.Based on the residual plot, which statement best explains whether the regression line is a good model for the data set and why?

# data[].attributes.body
The regression line is a good model because the points in the residual plot are close to the x-axis and randomly spread around the x-axis.

# data[].attributes.headline
The residual plot for a data set is shown.Based on the residual plot, which statement best explains whether the regression line is a good model for the data set and why?

# data[].attributes.subject
The residual plot for a data set is shown.Based on the residual plot, which statement best explains whether the regression line is a good model for the data set and why?

# data[].attributes.body
The regression line is not a good model because the residuals are not randomly distributed

# data[].attributes.headline
These are the values in Irwin’s data set.(1, 43), (3, 36), (5,22), (6, 25), (8,14)Irwin determined the equation of a linear regression line, and determined that these are the predicted values.(1, 44), (3, 35), (5,26), (6, 22), (8,13)Use the point tool to graph the residual plot for the data set.

# data[].attributes.subject
These are the values in Irwin’s data set.(1, 43), (3, 36), (5,22), (6, 25), (8,14)Irwin determined the equation of a linear regression line, and determined that these are the predicted values.(1, 44), (3, 35), (5,26), (6, 22), (8,13)Use the point tool to graph the residual plot for the data set.

# data[].attributes.body
Graph points at:
(3,1),(6,3),(8,1),(1,-1),(5,-4)

# data[].attributes.headline
These are the values in Ariel’s data set.(1, 67), (3, 88), (5,97), (6, 101), (8, 115)Ariel determines the equation of a linear regression line to be yˆ=6.5x+63.8 .Use the point tool to graph the residual plot for the data set.Round residuals to the nearest unit as needed.

# data[].attributes.subject
These are the values in Ariel’s data set.(1, 67), (3, 88), (5,97), (6, 101), (8, 115)Ariel determines the equation of a linear regression line to be yˆ=6.5x+63.8 .Use the point tool to graph the residual plot for the data set.Round residuals to the nearest unit as needed.

# data[].attributes.body
Graph points at:
(3,5),(5,1),(1,-3),(6,-2),(8,-1)

# data[].attributes.headline
Which answer is the best estimate of the residual value when x = 2?

# data[].attributes.subject
Which answer is the best estimate of the residual value when x = 2?

# data[].attributes.body
−0.5

# data[].attributes.headline
These are the values in Rita’s data set.(1, 19), (2, 33), (4,45), (5, 57), (6,71.5)Rita determines the equation of a linear regression line to be yˆ=9.7x+10.3 .Use the point tool to graph the residual plot for the data set.Round residuals to the nearest unit as needed.

# data[].attributes.subject
These are the values in Rita’s data set.(1, 19), (2, 33), (4,45), (5, 57), (6,71.5)Rita determines the equation of a linear regression line to be yˆ=9.7x+10.3 .Use the point tool to graph the residual plot for the data set.Round residuals to the nearest unit as needed.

# data[].attributes.body
Graph points at:
(2,3),(6,3),(1,-1),(4,-4),(5,-2)