Description Usage Format Details Source Examples
These times represent times between gondolas at Sterling Winery. The main take-away: there are 7 cars, as evidenced by the somewhat regular increases in splits between every 7 cars. The reason the times are slightly non-constant is that the gondolas come off the tracks, so times will change a little between each period.
1 | data("winery.cars")
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A data frame with 52 observations on the following 2 variables.
obs.number
The observation number, e.g. observation 3 was immediately preceded by observation 2.
time.until.next
Time until this gondola car arrived since the last car had left.
Important context: there was a sufficient line that people were leaving the winery.
So why is this data valuable? It indicates that the winery should add one more car since it has a lot of time wasted every 7th car. By adding another car, fewer visitors are likely to be turned away, resulting in increased revenue.
In-person data collection by David Diez (OpenIntro) on July 4th, 2013.
1 2 3 4 5 6 7 | data(winery.cars)
winery.cars$car.number <- rep(1:7, 10)[1:nrow(winery.cars)]
col <- COL[ifelse(winery.cars$car.number == 3, 4, 1)]
plot(winery.cars[, c("obs.number", "time.until.next")],
col = col, pch = 19)
plot(winery.cars$car.number, winery.cars$time.until.next,
col = fadeColor(col, "88"), pch = 19)
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