Difference between revisions of "Worksheets/Week2"

@@ Line 1: / Line 1: @@
-A baked food product:
-* T = time used to bake the product
-* F = quantity of fat added
 <html><div data-datacamp-exercise data-lang="r" data-height="auto">
      <code data-type="sample-code">
-# 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)
-# Make a prediction with this model:
-xT = -1   # corresponds to 110 minutes
-xF = -1   # corresponds to 20 grams of fat
-y.hat <- predict(model_crispy, data.frame(T = xT, F = xF))
-paste0('Predicted value is: ', y.hat, ' crispiness.')
      </code>
 </div></html>

Revision as of 08:44, 26 September 2019