Juliet: Juliet

In MPV: Data Sets from Montgomery, Peck and Vining

Juliet

Description

Juliet has 28 rows and 9 columns. The data is of the input and output of the Spirit Still "Juliet" from Endless Summer Distillery. It is suggested to split the data by the Batch factor for ease of use.

Usage

Juliet

Format

The data frame contains the following 9 columns.

Batch

a Factor determing how many times the volume has been through the still.

Vol1

Volume in litres, initial

P1

Percent alcohol present, initial

LAA1

Litres Absolute Alcohol initial, Vol1*P1

Vol2

Volume in litres, final

P2

Percent alcohol present, final

LAA2

Litres Absolute Alcohol final, Vol2*P2

Yield

Percent yield obtained, LAA2/LAA1

Date

Character, Date of run

Details

The purpose of this information is to determine the optimal initial volume and percentage. The information is broken down by Batch. A batch factor 1 means that it is the first time the liquid has gone through the spirit still. The first run through the still should have the most loss due to the "heads" and "tails". Literature states that the first run through a spirit still should yield 70 percent. A batch factor 2 means that it is the second time the liquid has gone through the spirit still. A batch factor 3 means that it is the third time or more that the liquid has gone through the spirit still. Each subsequent distillation should result in a higher yield, never to exceed 95 percent.

Source

Charisse Woods, Endless Summer Distillery, (2015).

Examples

summary(Juliet)

#Split apart the Batch factor for easier use.
juliet<-split(Juliet,Juliet$Batch)
juliet1<-juliet$'1'
juliet2<-juliet$'2'
juliet3<-juliet$'3'

plot(LAA1~LAA2,data=Juliet)
plot(LAA1~LAA2,data=juliet1)

MPV documentation built on Sept. 8, 2023, 5:44 p.m.