Difference between revisions of "Worksheets/Week2"

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# T = time used for baking: (-1) corresponds to 80 minutes and (+1) corresponds to 100 minutes
# T = time used for baking: (-1) corresponds to 80 minutes and (+1) corresponds to 100 minutes
A <- c(-1, +1, -1, +1)
T <- c(-1, +1, -1, +1)


# F = quantity of fat used: (-1) corresponds to 20 g and (+1) corresponds to 30 grams
# F = quantity of fat used: (-1) corresponds to 20 g and (+1) corresponds to 30 grams
B <- c(-1, -1, +1, +1)
F <- c(-1, -1, +1, +1)


# Response y is the crispiness
# Response y is the crispiness
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# Fit a linear model
# Fit a linear model
model_crispy <- lm(y ~ A + B + A*B)
model_crispy <- lm(y ~ T + F + T*F)
summary(model_crispy)
summary(model_crispy)



Revision as of 08:14, 26 September 2019

Worksheets Next step: Week3 →

A baked food product:

  • T = time used to bake the product
  • F = quantity of fat added

# T = time used for baking: (-1) corresponds to 80 minutes and (+1) corresponds to 100 minutes T <- c(-1, +1, -1, +1) # F = quantity of fat used: (-1) corresponds to 20 g and (+1) corresponds to 30 grams F <- c(-1, -1, +1, +1) # Response y is the crispiness y <- c(37, 57, 49, 53) # Fit a linear model model_crispy <- lm(y ~ T + F + T*F) summary(model_crispy) # Uncomment this line if you run the code in RStudio #library(pid) # Comment this line if you run this code in RStudio source('https://yint.org/contourPlot.R') # See how the two factors affect the response: contourPlot(model_crispy ) interaction.plot(T, F, y) interaction.plot(F, T, y)