R Dataset / Package MASS / whiteside

On this R-data statistics page, you will find information about the whiteside data set which pertains to House Insulation: Whiteside's Data. The whiteside data set is found in the MASS R package. You can load the whiteside data set in R by issuing the following command at the console data("whiteside"). This will load the data into a variable called whiteside. If R says the whiteside data set is not found, you can try installing the package by issuing this command install.packages("MASS") and then attempt to reload the data with the library() command. 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 whiteside R data set. The size of this file is about 913 bytes.

House Insulation: Whiteside's Data


Mr Derek Whiteside of the UK Building Research Station recorded the weekly gas consumption and average external temperature at his own house in south-east England for two heating seasons, one of 26 weeks before, and one of 30 weeks after cavity-wall insulation was installed. The object of the exercise was to assess the effect of the insulation on gas consumption.




The whiteside data frame has 56 rows and 3 columns.:


A factor, before or after insulation.


Purportedly the average outside temperature in degrees Celsius. (These values is far too low for any 56-week period in the 1960s in South-East England. It might be the weekly average of daily minima.)


The weekly gas consumption in 1000s of cubic feet.


A data set collected in the 1960s by Mr Derek Whiteside of the UK Building Research Station. Reported by

Hand, D. J., Daly, F., McConway, K., Lunn, D. and Ostrowski, E. eds (1993) A Handbook of Small Data Sets. Chapman & Hall, p. 69.


Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.


xyplot(Gas ~ Temp | Insul, whiteside, panel =
function(x, y, ...) {
panel.xyplot(x, y, ...)
panel.lmline(x, y, ...)
}, xlab = "Average external temperature (deg. C)",
ylab = "Gas consumption(1000 cubic feet)", aspect = "xy",
strip = function(...) strip.default(..., style = 1))gasB <- lm(Gas ~ Temp, whiteside, subset = Insul=="Before")
gasA <- update(gasB, subset = Insul=="After")
gasBA <- lm(Gas ~ Insul/Temp - 1, whiteside)
summary(gasBA)gasQ <- lm(Gas ~ Insul/(Temp + I(Temp^2)) - 1, whiteside)
coef(summary(gasQ))gasPR <- lm(Gas ~ Insul + Temp, whiteside)
anova(gasPR, gasBA)
options(contrasts = c("contr.treatment", "contr.poly"))
gasBA1 <- lm(Gas ~ Insul*Temp, whiteside)

Dataset imported from https://www.r-project.org.

Attachments: csv, json

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