Apartments in Vitoria

Source: R/AgainStart.R

Descriptive information and the appraised total price (in Euros) for apartments in Vitoria, Spain

VIT2005

Format

A data frame with 218 observations on the following 5 variables:

  • totalprice (the market total price (in Euros) of the apartment including garage(s) and storage room(s))

  • area (the total living area of the apartment in square meters)

  • zone (a factor indicating the neighborhood where the apartment is located with levels Z11, Z21, Z31, Z32, Z34, Z35, Z36, Z37, Z38, Z41, Z42, Z43, Z44, Z45, Z46, Z47, Z48, Z49, Z52, Z53, Z56, Z61, and Z62)

  • category (a factor indicating the condition of the apartment with levels 2A, 2B, 3A, 3B, 4A, 4B, and 5A ordered so that 2A is the best and 5A is the worst)

  • age (age of the apartment in years)

  • floor (floor on which the apartment is located)

  • rooms (total number of rooms including bedrooms, dining room, and kitchen)

  • out (a factor indicating the percent of the apartment exposed to the elements: The levels E100, E75, E50, and E25, correspond to complete exposure, 75% exposure, 50% exposure, and 25% exposure, respectively.)

  • conservation (is an ordered factor indicating the state of conservation of the apartment. The levels 1A, 2A, 2B, and 3A are ordered from best to worst conservation.)

  • toilets (the number of bathrooms)

  • garage (the number of garages)

  • elevator (indicates the absence (0) or presence (1) of elevators.)

  • streetcategory (an ordered factor from best to worst indicating the category of the street with levels S2, S3, S4, and S5)

  • heating (a factor indicating the type of heating with levels 1A, 3A, 3B, and 4A which correspond to: no heating, low-standard private heating, high-standard private heating, and central heating, respectively.)

  • storage (the number of storage rooms outside of the apartment)

References

Ugarte, M. D., Militino, A. F., and Arnholt, A. T. 2015. Probability and Statistics with R, Second Edition. Chapman & Hall / CRC.

Examples

ggplot(data = VIT2005, aes(x = area, y = totalprice, color = factor(elevator))) + 
geom_point()

modTotal <- lm(totalprice ~ area + as.factor(elevator) + area:as.factor(elevator), 
data = VIT2005)
modSimpl <- lm(totalprice ~ area, data = VIT2005)
anova(modSimpl, modTotal)
#> Analysis of Variance Table
#> 
#> Model 1: totalprice ~ area
#> Model 2: totalprice ~ area + as.factor(elevator) + area:as.factor(elevator)
#>   Res.Df        RSS Df Sum of Sq      F    Pr(>F)    
#> 1    216 3.5970e+11                                  
#> 2    214 3.0267e+11  2 5.704e+10 20.165 9.478e-09 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
rm(modSimpl, modTotal)