R is a very powerful program, in part because statisticians and data scientists can build specialized sets of programs that you can load and run in R. In this assignment, we learn to load and use a very popular set of packages called tidyverse. You will use a built-in R dataset, mtcars, which contains data on 32 automobiles (models) from a 1974 Motor Trend magazine. "# Convert mtcars to a tibble and make the row names a new column # The column 'model' will contain the car names (e.g., 'Mazda RX4') data_cars <- mtcars %>% rownames_to_column(var = Fiat500L") %>% as_tibble() # View the structure of the data to understand the variables head(data_cars) str(data_cars) #you can learn about the data set (variable names and explanations and the source of the data) with this command ?mtcars. "Task 3: Filtering and Visualizing a Continuous Variable (3 points) We will examine the distribution of hp (gross horsepower) for a specific subgroup