dressing: Dressing data
In ffmanova: Fifty-Fifty MANOVA
dressing R Documentation
Dressing data
Description
A dataset from an experiment studying structural and rheological properties
of a full fat dressing.
Usage
data(dressing)
Format
A data frame with 29 observations on the following 7 variables.
- press
a numeric vector with values 75, 125 and
225. The homogenisation pressure.
- stab
a numeric vector
with values 0.3, 0.4 and 0.5. Amount of stabiliser.
- emul
a
numeric vector with values 0.1, 0.2 and 0.35. Amount of emulsifier.
- day
a factor with levels 1, ..., 5. The
day the experimental run was performed on.
- visc
a numeric
vector. The measured viscosity of the dressing.
- rheo
a
matrix with 9 columns. Nine different response-parameters derived from
rheological measuring. These parameters contain information about the
physics of the dression (more general that viscosity).
- pvol
a matrix with 241 columns. Particle-volume curves.
Using a coulter-counter instrument fat particles were counted and their
volumes were registered. These data are presented as smoothed histograms
(equally spaced bins on log-scale). The total area under the curve
represents the total volume of the counted fat particles. The shape of the
curve reflects how the total fat volume is distributed among the different
particle sizes.
Details
The data comes from an experiment in which full fat dressings were produced
with different amount of stabiliser and emulsifier, and with different
homogenisation pressure (se above).
A full factorial 3^3 design with two additional center points was
used. The experiment was run over five days. It was unknown up front how
many experimental runs could be performed each day, so the order of the runs
was randomised.
For each dressing, viscosity, rheology and particle volume measurements were
taken (se above).
The day is stored as a factor. The other design variables are stored as
numerical variables. If one wants to use them as factors, one can use e.g.
factor(press) in the model formula, or
dressing$press <- factor(dressing$press)
prior to calling the modelling function.
Source
The data is taken from a research project financed by a grant
(131472/112) from the Norwegian Research Council. The project was managed
by Stabburet, which is a major manufacturer of dressing in Norway.
ffmanova documentation built on Oct. 18, 2023, 5:08 p.m.
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| dressing | R Documentation |
Dressing data
Description
A dataset from an experiment studying structural and rheological properties of a full fat dressing.
Usage
data(dressing)
Format
A data frame with 29 observations on the following 7 variables.
- press
a numeric vector with values 75, 125 and 225. The homogenisation pressure.
- stab
a numeric vector with values 0.3, 0.4 and 0.5. Amount of stabiliser.
- emul
a numeric vector with values 0.1, 0.2 and 0.35. Amount of emulsifier.
- day
a factor with levels
1, ...,5. The day the experimental run was performed on.- visc
a numeric vector. The measured viscosity of the dressing.
- rheo
a matrix with 9 columns. Nine different response-parameters derived from rheological measuring. These parameters contain information about the physics of the dression (more general that viscosity).
- pvol
a matrix with 241 columns. Particle-volume curves. Using a coulter-counter instrument fat particles were counted and their volumes were registered. These data are presented as smoothed histograms (equally spaced bins on log-scale). The total area under the curve represents the total volume of the counted fat particles. The shape of the curve reflects how the total fat volume is distributed among the different particle sizes.
Details
The data comes from an experiment in which full fat dressings were produced with different amount of stabiliser and emulsifier, and with different homogenisation pressure (se above).
A full factorial 3^3 design with two additional center points was
used. The experiment was run over five days. It was unknown up front how
many experimental runs could be performed each day, so the order of the runs
was randomised.
For each dressing, viscosity, rheology and particle volume measurements were taken (se above).
The day is stored as a factor. The other design variables are stored as
numerical variables. If one wants to use them as factors, one can use e.g.
factor(press) in the model formula, or
dressing$press <- factor(dressing$press)
prior to calling the modelling function.
Source
The data is taken from a research project financed by a grant (131472/112) from the Norwegian Research Council. The project was managed by Stabburet, which is a major manufacturer of dressing in Norway.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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