The true statement about the lines of best fit for the two data sets is (a) The y-intercepts of the lines of best fit for data sets A and B differ by 4, but the slopes are the same.
How to interpret the lines of best fit of both datasets
The slopes
From the dataset, we can see that the datasets A and B are both linear regressions; this is so because the lines of both graphs increase in a linear model
Also, the distance between corresponding points of the datasets are equal, this means that they have the same slope
The y-intercept
When the line of best fit of dataset A is traced, it crosses the y-axis at:
y= 3
When the line of best fit of dataset B is traced, it crosses the y-axis at:
y= -1
The difference (d) is then calculated as:
d = 3 - (-1)
Evaluate the difference
d = 4
This means that, their y-intercepts differ by 4
Hence, the y-intercepts of the lines of best fit for data sets A and B differ by 4, but the slopes are the same.
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