Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

bottling

A Three Factorial Experiment for Bottling Data


Description

The height of the fills in the soft drink bottle is required to be as consistent as possible and it is controlled through three factors: (i) the percent carbonation of the drink, (ii) the operating pressure in the filler, and (iii) the line speed which is the number of bottles filled per minute. The first factor variable of the percent of carbonation is available at three levels of 10, 12, and 14, the operating pressure is at 25 and 30 psi units, while the line speed are at 200 and 250 bottles per minute. Two complete replicates are available for each combination of the three factor levels, that is, 24 total number of observations. In this experiment, the deviation from the required height level is measured.

Usage

data(bottling)

Format

A data frame with 24 observations on the following 4 variables.

Deviation

deviation from required height level

Carbonation

the percent carbonation of the drink

Pressure

the operating pressure in the filler

Speed

the number of bottles filled per minute

Source

Montgomery, D. C. (1976-2012). Design and Analysis of Experiments, 8e. J.Wiley.

Examples

data(bottling)
summary(bottling.aov <- aov(Deviation~.^3,bottling))
# Equivalent way
summary(aov(Deviation~ Carbonation + Pressure + Speed+ (Carbonation*Pressure)+
(Carbonation*Speed)+(Pressure*Speed)+(Carbonation*Speed*Pressure),data=bottling))

ACSWR

A Companion Package for the Book "A Course in Statistics with R"

v1.0
GPL-2
Authors
Prabhanjan Tattar
Initial release
2015-09-05

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.