Difference between revisions of "Worksheets/Week3"
Kevin Dunn (talk | contribs) (→Part 5) |
Kevin Dunn (talk | contribs) (→Part 5) |
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<html><div data-datacamp-exercise data-lang="r" data-height=" | <html><div data-datacamp-exercise data-lang="r" data-height="auto"> | ||
<code data-type="sample-code"> | <code data-type="sample-code"> | ||
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# B: feed concentration: -1 == 5%; +1 == 15% | # B: feed concentration: -1 == 5%; +1 == 15% | ||
# C: mixer type: -1 = R mixer; +1 = W mixer | # C: mixer type: -1 = R mixer; +1 = W mixer | ||
mod.stability <- lm(y ~ A*B*C) | mod.stability <- lm(y ~ A*B*C) | ||
summary(mod.stability) | summary(mod.stability) | ||
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# Uncomment this line if you run the code in RStudio | # Uncomment this line if you run the code in RStudio | ||
#library(pid) | #library(pid) | ||
# Comment | # Comment these 2 lines if you run this code in RStudio | ||
source('https://yint.org/paretoPlot.R') | source('https://yint.org/paretoPlot.R') | ||
source('https://yint.org/contourPlot.R') | source('https://yint.org/contourPlot.R') | ||
Revision as of 16:39, 10 March 2019
Part 1
A factorial experiment was run to investigate the settings that minimize the production of an unwanted side product. The two factors being investigated are called A and B for simplicity.
Part 2
Continuing from above, with 2 extra experimental points:
Part 3
Your family runs a small business selling products online. The first factor of interest is whether to provide free shipping over €30 or over €50. The second factor is whether or not the purchaser must first create a profile before completing the transaction. The purchaser can still complete their transaction without creating a profile. Below are the data collected, showing the 8 experiments.
Part 4
Continuing with the case above:
Part 5
Your group is developing a new product, but have been struggling to get the product’s stability, measured in days, to the level required. You are aiming for a stability value of 50 days or more.
base <- c(-1, +1) design <- expand.grid(A=base, B=base, C=base) A <- design$A B <- design$B C <- design$C y <- c(40, 27, 35, 21, 41, 27, 31, 20) mod.stability <- lm(y ~ A*B*C) summary(mod.stability) paretoPlot(mod.stability) contourPlot(mod.stability, 'A', 'B') contourPlot(mod.stability, 'A', 'C')