golf: Full factorial experiments to maximize a golfer's driving...
In pid: Process Improvement using Data
golf R Documentation
Full factorial experiments to maximize a golfer's driving distance.
Description
A full factorial experiment with four factors run by a golf enthusiast. The
objective of the experiments was for the golfer to maximize her driving distance
at a specific tee off location on her local golf course. The golfer considered
the following factors:
-
T = Tee height (cm)
-
H = Holes the golf ball had been played for prior to the experimental tee shot
-
C = Club type
-
D = Time of day (on the 24 hour clock)
The data are in standard order, however the actual experiments were run in
random order.
Coded values for A, B, C, and D should be used in the linear
regression model analysis, with -1 representing the low value and +1 the
high value.
Usage
data(golf)
Format
A data.frame containing 16 observations of 4 variables (A, B, C, D, with y as a response variable.)
Source
A MOOC on Design of Experiments: “Experimentation for Improvement”, https://learnche.org
pid documentation built on Jan. 10, 2026, 5:07 p.m.
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| golf | R Documentation |
Full factorial experiments to maximize a golfer's driving distance.
Description
A full factorial experiment with four factors run by a golf enthusiast. The objective of the experiments was for the golfer to maximize her driving distance at a specific tee off location on her local golf course. The golfer considered the following factors:
-
T= Tee height (cm) -
H= Holes the golf ball had been played for prior to the experimental tee shot -
C= Club type -
D= Time of day (on the 24 hour clock)
The data are in standard order, however the actual experiments were run in random order.
Coded values for A, B, C, and D should be used in the linear
regression model analysis, with -1 representing the low value and +1 the
high value.
Usage
data(golf)Format
A data.frame containing 16 observations of 4 variables (A, B, C, D, with y as a response variable.)
Source
A MOOC on Design of Experiments: “Experimentation for Improvement”, https://learnche.org
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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