To find the y-intercept of the line of fit that passes through the points \(0, 40\) and \(2, 70\), we can use the general form of the equation for a line, which is \(y = mx + b\), where \(m\) is the slope and \(b\) is the y-intercept.
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Calculate the slope (m): The slope can be calculated using the two points \( (0, 40) \) and \( (2, 70) \):
\[ m = \frac{y_2 - y_1}{x_2 - x_1} = \frac{70 - 40}{2 - 0} = \frac{30}{2} = 15 \]
So, the slope \(m\) is \(15\).
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Find the y-intercept (b): We already have one of the points, \( (0, 40) \), which directly gives us the y-intercept:
\[ b = 40 \]
This means that when \(x = 0\) (i.e., when a student has studied for 0 hours), the predicted value of \(y\) (the grade) is 40%.
Meaning in the context of the data: The y-intercept of 40 implies that a student who studies for 0 hours is predicted to earn 40% on the test.
Therefore, the correct answer is:
40; a student who studies for 0 hours is predicted to earn 40% on the test.