Fitting Linear Models to Data · Exercise 1

The data below shows the relationship between the mass of an automobile (measured in kg) and the fuel efficiency of the car (measured in miles per gallon) for 7 automobiles.
$$\begin{array}{cccccccc}\text{Mass (kg), x}& \text{1305}& \text{1150}& \text{1925}& \text{1628}& \text{1506}& \text{1452}& \text{1835}\\ \text{Fuel Efficiency (MPG), y}& \text{27}& \text{28}& \text{15}& \text{24}& \text{23}& \text{25}& \text{19}\end{array}$$

ⓐ Draw a scatter plot (by hand or using a graphing utility) for the data provided being sure to label your axes.
ⓑ Does the data appear to be linearly related? Is the association between the variables positive or negative?
ⓒ Choose two points that seem to represent the general pattern in the data set. Write these points as ordered pairs below.
$\left(,\right)$
$\left(,\right)$
ⓓ Write the equation of the line passing through the points you listed in part c. in slope intercept form. Show your work below.
ⓔ Use the linear function you found in part d. to predict the fuel efficiency of an Audi A5 Quattro whose mass is 1610 kg.

Its source prints no answer for this problem, so there's nothing to check against.

OpenStax, Algebra and Trigonometry 2e · §4.3 Fitting Linear Models to Data · Exercise 1