fit model pages (see #2395)

lessons/Data-Science/fitting-models/langs/en-us/pages/intro-fit-model.adoc

@@ -1,4 +1,3 @@
-[.landscape]
 = Introducing fit-model
 
 [.linkInstructions]
@@ -7,24 +6,39 @@ These data visualizations were generated using the @starter-file{fitting-animals
 [cols="1a,1a", frame="none", options="header"]
 |===
 | `fun cy(x): (-3 * x) + 23 end` +
-`fit-model(lizard-sample, "name", "pounds", "weeks", cy)`
+`fit-model(` +
+@hspace{1em} `lizard-sample, "name", "pounds", "weeks", cy)`
 | `fun jo(x): (-0.8 * x) + 10.4 end` +
-`fit-model(lizard-sample, "name", "pounds", "weeks", jo)`
+`fit-model(` +
+@hspace{1em} `lizard-sample, "name", "pounds", "weeks", jo)`
 
 ^| @image{../images/fit-cy-crop.png}
 ^| @image{../images/fit-jo-crop.png}
 |===
 
-@n What do you Notice? @fitb{}{}
+[.FillVerticalSpace, cols="1a,1a", options="header"]
+|===
+| What do you Notice?
+| What do you Wonder?
 
-@fitb{}{}
+|
+|
+|===
+
+@n How is the `fit-model` plot for cy's model similar to the `fit-model` plot for jo's model? @fitb{}{}
 
 @fitb{}{}
 
+@fitb{}{}
 
-@n What do you Wonder? @fitb{}{}
+@n How is the `fit-model` plot for cy's model different from the `fit-model` plot for jo's model? @fitb{}{}
 
 @fitb{}{}
 
 @fitb{}{}
 
+@n What do you think the three terms in the legend refer to?
+
+- Model: @fitb{}{}
+- Data: @fitb{}{}
+- Residuals: @fitb{}{}

lessons/Data-Science/fitting-models/langs/en-us/pages/s-tells-us.adoc

@@ -11,62 +11,62 @@ For each model below, decide whether the fit is "poor", "ok", or "good". _Then_
   * The range of days to adoption in this dataset are from 0 to 400. 
   * An @math{S} value of 300 means predicted adoption times could be off by 300 days.  
 
-This is a(n) @fitbruby{25em}{@ifsoln{good}}{poor, ok, good} model for the dataset.
-| @ifsoln{7 or 8}
+I @fitbruby{18em}{@ifsoln{strongly disagree}}{strongly agree, agree, disagree, strongly disagree} that this model is a good fit.
+| @ifsoln{7}
 
 | @n A student is exploring a dataset on climate change.
 
   * The range of Arctic Sea Ice is from 3,920,000 to 7,670,000 square kilometers
   * An @math{S} value of 300 means predicted Arctic Sea Ice coverage could be off by 300 square kilometers.
 
-This is a(n) @fitbruby{25em}{@ifsoln{good}}{poor, ok, good} model for the dataset.
+I @fitbruby{18em}{@ifsoln{strongly agree}}{strongly agree, agree, disagree, strongly disagree} that this model is a good fit.
 | @ifsoln{1 or 2}
 
 | @n A data scientist is working with data from US public schools.
 
   * The range of graduates per school per year is 2 to 2003. 
   * An @math{S} value of 300 means predicted graduate values could be off by 300 students.  
 
-This is a(n) @fitbruby{25em}{@ifsoln{poor}}{poor, ok, good} model for the dataset.
-| @ifsoln{6}
+I @fitbruby{18em}{@ifsoln{disagree}}{strongly agree, agree, disagree, strongly disagree} that this model is a good fit.
+| @ifsoln{5 or 6}
 
 | @n A student is exploring a dataset on earthquakes.
 
   * The range of earthquake depths in this dataset are from 4200m to 664000m. 
   * An @math{S} value of 300 means predicted earthquake depths could be off by 300 meters.  
 
-This is a(n) @fitbruby{25em}{@ifsoln{good}}{poor, ok, good} model for the dataset.
+I @fitbruby{18em}{@ifsoln{strongly agree}}{strongly agree, agree, disagree, strongly disagree} that this model is a good fit.
 | @ifsoln{3 or 4}
 
 | @n A student is exploring a dataset on arrests in Los Angeles.
 
   * The age range in this dataset is from 0 to 92. 
   * An @math{S} value of 1 means predicted ages could be off by 1 year.  
 
-This is a(n) @fitbruby{25em}{@ifsoln{good}}{poor, ok, good} model for the dataset.
+I @fitbruby{18em}{@ifsoln{agree}}{strongly agree, agree, disagree, strongly disagree} that this model is a good fit.
 | @ifsoln{3 or 4}
 
 | @n A data scientist is working with data about snowflakes.
 
   * The range of snowflake weights is from 0.001 grams to 0.02 grams. 
   * An @math{S} value of 1 means predicted values could be off by 1 gram.  
 
-This is a(n) @fitbruby{25em}{@ifsoln{poor}}{poor, ok, good} model for the dataset.
-| @ifsoln{7 or 8}
+I @fitbruby{18em}{@ifsoln{strongly disagree}}{strongly agree, agree, disagree, strongly disagree} that this model is a good fit.
+| @ifsoln{8}
 
 | @n A data scientist is working with data from animals at a shelter.
 
   * The range of ages is from 0.5 years to 16 years. 
   * An @math{S} value of 1 means predicted ages could be off by 1 year.  
 
-This is a(n) @fitbruby{25em}{@ifsoln{ok}}{poor, ok, good} model for the dataset.
-| @ifsoln{5}
+I @fitbruby{18em}{@ifsoln{agree}}{strongly agree, agree, disagree, strongly disagree} that this model is a good fit.
+| @ifsoln{5 or 6}
 
 | @n A student is working with a dataset of adult blue whales.
 
   * The range of weights is 200,000 to 330,000 pounds. 
   * An @math{S} value of 1 means predicted weights could be off by 1 pound.  
 
-This is a(n) @fitbruby{25em}{@ifsoln{good}}{poor, ok, good} model for the dataset.
+I @fitbruby{18em}{@ifsoln{strongly agree}}{strongly agree, agree, disagree, strongly disagree} that this model is a good fit
 | @ifsoln{1 or 2}
 |===