small change to project text

doc/src/week38/exercisesweek38.do.txt

@@ -39,7 +39,6 @@ Here the expected value $\mathbb{E}$ is the sample value.
 
 Show that you can rewrite  this in terms of a term which contains the variance of the model itself (the so-called variance term), a
 term which measures the deviation from the true data and the mean value of the model (the bias term) and finally the variance of the noise.
-
 That is, show that
 !bt
 \[
@@ -55,11 +54,10 @@ with
 and 
 !bt
 \[
-\mathrm{var}[\tilde{y}]=\frac{1}{n}\sum_i(\tilde{y}_i-\mathbb{E}\left[\bm{\tilde{y}}\right])^2.
+\mathrm{var}[\tilde{y}]=\mathbb{E}\left[\left(\tilde{\bm{y}}-\mathbb{E}\left[\bm{\tilde{y}}\right]\right)^2\right]=\frac{1}{n}\sum_i(\tilde{y}_i-\mathbb{E}\left[\bm{\tilde{y}}\right])^2.
 \]
 !et
-The answer to this exercise should be included in the theory part of the report.  This exercise is also part of the weekly exercises of week 37.
-Explain what the terms mean and discuss their interpretations.
+
 
 
 Explain what the terms mean and discuss their interpretations.
@@ -76,3 +74,4 @@ You can follow the code example in the jupyter-book at URL:"https://compphysics.
 See also the whiteboard notes from week 37 at URL:"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep14.pdf"
 
 
+