# R Dataset / Package DAAG / carprice

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dataset-70618.csv | 2.03 KB |

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On this Picostat.com statistics page, you will find information about the carprice data set which pertains to US Car Price Data. The carprice data set is found in the DAAG R package. You can load the carprice data set in R by issuing the following command at the console data("carprice"). This will load the data into a variable called carprice. If R says the carprice data set is not found, you can try installing the package by issuing this command install.packages("DAAG") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the carprice R data set. The size of this file is about 2,076 bytes. ## US Car Price Data## DescriptionU.S. data extracted from ## Usagecarprice ## FormatThis data frame contains the following columns: - Type
Type of car, e.g. Sporty, Van, Compact - Min.Price
Price for a basic model - Price
Price for a mid-range model - Max.Price
Price for a ‘premium’ model - Range.Price
Difference between Max.Price and Min.Price - RoughRange
Rough.Range plus some N(0,.0001) noise - gpm100
The number of gallons required to travel 100 miles - MPG.city
Average number of miles per gallon for city driving - MPG.highway
Average number of miles per gallon for highway driving
## SourceMASS package ## ReferencesVenables, W.N.\ and Ripley, B.D., 4th edn 2002. Modern Applied Statistics with S. Springer, New York. See also ‘R’ Complements to Modern Applied Statistics with S-Plus, available from http://www.stats.ox.ac.uk/pub/MASS3/ ## Examplesprint("Multicollinearity - Example 6.8") pairs(carprice[,-c(1,8,9)])carprice1.lm <- lm(gpm100 ~ Type+Min.Price+Price+Max.Price+Range.Price, data=carprice) round(summary(carprice1.lm)$coef,3) pause()alias(carprice1.lm) pause()carprice2.lm <- lm(gpm100 ~ Type+Min.Price+Price+Max.Price+RoughRange, data=carprice) round(summary(carprice2.lm)$coef, 2) pause()carprice.lm <- lm(gpm100 ~ Type + Price, data = carprice) round(summary(carprice.lm)$coef,4) pause()summary(carprice1.lm)$sigma # residual standard error when fitting all 3 price variables pause()summary(carprice.lm)$sigma # residual standard error when only price is used pause()vif(lm(gpm100 ~ Price, data=carprice)) # Baseline Price pause()vif(carprice1.lm) # includes Min.Price, Price & Max.Price pause()vif(carprice2.lm) # includes Min.Price, Price, Max.Price & RoughRange pause()vif(carprice.lm) # Price alone -- Dataset imported from https://www.r-project.org. |

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