R/BSDA-package.R
Bumpers.Rd
Data for Exercise 1.73
Bumpers
A data frame/tibble with 23 observations on two variables
a factor with levels Buick Century
,
Buick Skylark
, Chevrolet Cavalier
, Chevrolet Corsica
,
Chevrolet Lumina
, Dodge Dynasty
, Dodge Monaco
, Ford
Taurus
, Ford Tempo
, Honda Accord
, Hyundai Sonata
,
Mazda 626
, Mitsubishi Galant
, Nissan Stanza
,
Oldsmobile Calais
, Oldsmobile Ciere
, Plymouth Acclaim
,
Pontiac 6000
, Pontiac Grand Am
, Pontiac Sunbird
,
Saturn SL2
, Subaru Legacy
, and Toyota Camry
total repair cost (in dollars) after crashing a car into a barrier four times while the car was traveling at 5 miles per hour
Insurance Institute of Highway Safety.
Kitchens, L. J. (2003) Basic Statistics and Data Analysis. Pacific Grove, CA: Brooks/Cole, a division of Thomson Learning.
EDA(Bumpers$repair)
#> [1] "Bumpers$repair"
#> Size (n) Missing Minimum 1st Qu Mean Median TrMean
#> 23.000 0.000 618.000 1456.000 2122.478 2129.000 2138.143
#> 3rd Qu Max. Stdev. Var. SE Mean I.Q.R. Range
#> 3002.000 3298.000 798.457 637534.170 166.490 1546.000 2680.000
#> Kurtosis Skewness SW p-val
#> -1.140 -0.080 0.287
stripchart(Bumpers$repair, method = "stack", pch = 19, col = "blue")
library(lattice)
dotplot(car ~ repair, data = Bumpers)