We expect a car’s highway gas mileage to be related to its city gas mileage. Suppose that we collect data on $n vehicles manufactured by one particular automaker and calculate the following regression line:
y = $a + $bx
where y is highway mileage and x is city mileage.
Use this regression line equation to calculate the predicted highway mileage for three new car models produced by this automaker.
The slope in a regression equation represents the value that DB8eX8yodOo= is 107jI2pFGFf9afifjyK8R1b1wb67i/Fq by in the regression equation.
The slope of this line means that XrMEveATiHYl0wQl mileage increases by about iSba6t70dtA= when p+QuAfKR2Uk= mileage increases by 0VV1JcqyBrI= mile per gallon.
The slope in this regression equation (to 3 decimal places) is: Mn7/H2oYk/BAUgn7
The intercept is the value, according to the regression equation, of OoQWwj+vEeo= when DB8eX8yodOo= = 1Wh3cvJ2xF4=.
The intercept in this regression equation (to 2 decimal places) is: DJMxM7tLNDmruLrq
Calculate predicted highway mileages for car models with the following three city mileages (round each prediction to 3 decimal places):
city mileage: | $x1 | $x2 | $x3 |
---|---|---|---|
predicted highway mileage: | iCOO6WQ0p4rRu2K3 | plQ7h/t1K2xpXajo | lHYXL5+2sZATad7+ |