Just another update

Task/Multiple-regression/00DESCRIPTION

@@ -9,4 +9,5 @@ Compute the vector <math>\beta = \{ \beta_1, \beta_2, ..., \beta_k \}</math> usi
 
 <math>y_j = \Sigma_i \beta_i \cdot x_{ij} ,    j \in 1..n</math>
 
-You can assume <i>y</i> is given to you as a vector (a one-dimensional array), and <i>X</i> is given to you as a two-dimensional array (i.e. matrix).
+You can assume <i>y</i> is given to you as a vector (a one-dimensional array),
+and <i>X</i> is given to you as a two-dimensional array (i.e. matrix).

Task/Multiple-regression/J/multiple-regression-3.j

@@ -3,4 +3,7 @@
                                  NB. |:X is transpose of X
 
    (%.(|:X) mp X) mp (|:X) mp y
+128.814 _143.163 61.9606
+   xpy=: mp~ |:                  NB. Or factoring out "X prime y" (monadically "X prime X")
+   X (%.@:xpy@[ mp xpy) y
 128.814 _143.163 61.9606

Task/Multiple-regression/Racket/multiple-regression-2.rkt

@@ -6,5 +6,5 @@
               [2]
               [3]
               [9]]))
-; Output:
+{{out}}
 (array #[#[9 1/3] #[-3 1/3]])

Task/Multiple-regression/Ruby/multiple-regression-3.rb

@@ -0,0 +1 @@
+puts regression_coefficients([3,4,5], [ [1,2,1], [1,1,2] ])