The file contains complete data for 392 cars that were sold in the U.S. between 1970 and 1982.

The objective of the analysis is to predict their fuel economy from various physical attributes. Description as below,

MPG : Miles per gallon

GallonsPer100Miles : Gallons per 100 Miles = 100/MPG

Cylinder : number of cylinders

Weight1000lb: Weight of car in 1000s of pounds

Displacement100ci: Engine displacement in 100s of cubic inches

Horsepower100: 100s of horsepower

1. Are these measurement or categorical variables?
2. Make a histogram for Gallons per 100 miles. (Choose 10-20 same size bins.)
3. Plot the following scatterplots (Remember to correctly label axes, scale, title):
   1. GallonsPer100Miles vs Displacement100ci
   2. GallonsPer100Miles vs Weight1000lb
   3. GallonsPer100Miles vs Horsepower100
4. Find the following correlations:
   1. GallonsPer100Miles vs Displacement100ci 0.866
   2. GallonsPer100Miles vs Weight1000lb
   3. GallonsPer100Miles vs Horsepower100
5. Which variable has the strongest linear relationship with GallonsPer100Miles? Is the correlation positive or negative? What does it signify?
6. Regression

Aim : To predict fuel economy(or Gallons per 100 Miles) from the variable in previous part.

6. 1. Get the regression equation in excel. Plot the regression line on the scatterplot.
   2. What is the slope and intercept?
   3. Interpret the intercept and slope.
7. Predict fuel economy for a car of weight 2500lbs.