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BADM 371 Intro to Data Analytics

14 Linear Regression with mtcars

Remember: ~ here means “explained by”, so the formula mpg ~ wt means we are predicting mpg as explained by wt. The most helpful way to view the output is with:

14.1 Excercises for you

14.1.1 mtcars

  1. Which variable in the mtcars dataset do you think best predicts mpg and why?
  2. What mpg would you predict for a car with a displacement of 333?
  3. What mpg would you predict for a car with a displacement of 12 cylinders?
  4. What mpg would you predict for a car with a displacement of 333 and 12 cylinders?
  5. What mpg would you predict for a car with a displacement of 333, 12 cylinders, and weighs 4,000 pounds?

14.1.2 trees

Open the trees dataset in R.

  1. What are the variables and what do they mean?
  2. Make a plot with Volume on the x axis and Height on the Y and add a best fit line.
  3. Use Girth and Height to predict Volume. What would you predict for a tree with a Girth of 10 and a Height of 100 feet?
  4. Use Girth and Height to predict Volume. What would you predict for a tree with a Girth of 10 and a Height of 15 meters?
  5. What is the maximum circumference of a tree in this dataset?

14.2 More Excercises for you

1.Open the women data set. Add a new variable (column) to the women dataframe called GPA which is these 15 numbers: 1.5, 3.7, 4,1, 3, 2.5, 3.8, 0.8, 2, 4, 1, 3, 2.5, 3.0, 4.0. You shoud get something that looks similar to mine.

FALSE    height weight GPA
FALSE 1      58    115 1.5
FALSE 2      59    117 3.7
FALSE 3      60    120 4.0
FALSE 4      61    123 1.0
FALSE 5      62    126 3.0
FALSE 6      63    129 2.5
FALSE 7      64    132 3.8
FALSE 8      65    135 0.8
FALSE 9      66    139 2.0
FALSE 10     67    142 4.0
FALSE 11     68    146 1.0
FALSE 12     69    150 3.0
FALSE 13     70    154 2.5
FALSE 14     71    159 3.0
FALSE 15     72    164 4.0

  1. Use GPA and weight to predict the height of a person who is 155 pounds and has a GPA if 3.33. What is your prediction?

  2. Is GPA a significant predictor of height and how do you know?

  3. Create a figure showing a best fit line on of height and GPA.

  4. Install the dplyr package into your Rstudio session.