--- a/lstsq/questions.rst	Tue Oct 12 10:36:46 2010 +0530
+++ b/lstsq/questions.rst	Tue Oct 12 10:47:28 2010 +0530
@@ -8,6 +8,8 @@
    #. [1.0, 1.0, 1.0]
    #. Error
    
+   Answer: array([1, 1, 1])
+   
  2. What does ones_like([1.2, 3, 4, 5]) produce
 
    a. [1.2, 3, 4, 5]
@@ -15,4 +17,16 @@
    #. array([1, 1, 1, 1])
    #. array([1.2, 3, 4, 5])
 
+   Answer: array([1.0, 1.0, 1.0, 1.0])
 
+ 3. The plot of ``u`` vs ``v`` is a bunch of scattered points that show a
+    linear trend. How do you find the least square fit line of ``u`` vs ``v``.
+
+   Answer::
+
+      A = array(u, ones_like(u)).T
+      result = lstsq(A, v)
+      m, c = result[0]
+
+      lst_line = m * u + c
+

--- a/lstsq/quickref.tex	Tue Oct 12 10:36:46 2010 +0530
+++ b/lstsq/quickref.tex	Tue Oct 12 10:47:28 2010 +0530
@@ -1,11 +1,15 @@
-Creating a tuple:\\
-{\ex \lstinline|    t = (1, "hello", 2.5)|}
+Creating a matrix with all ones:\\
+{\ex \lstinline|    o = ones_like(l)|}
 
-Accessing elements of tuples:\\
-{\ex \lstinline|    t[index] Ex: t[2]|}
+Creating the A matrix:\\
+{\ex \lstinline|    A = array(l, ones_like(l)).T|}
 
-Accessing slices of tuples:\\
-{\ex \lstinline|    t[start:stop:step]|}
+Computing least square:\\
+{\ex \lstinline|    result = lstsq(A, tsq)|}
 
-Swapping values:\\
-{\ex \lstinline|    a, b = b, a|}
+Obtaining the m and c values:\\
+{\ex \lstinline|    m, c = result[0]|}
+
+Computing the least square fit line:\\
+{\ex \lstinline|    lst_line = m * l + c|}
+

--- a/lstsq/script.rst	Tue Oct 12 10:36:46 2010 +0530
+++ b/lstsq/script.rst	Tue Oct 12 10:47:28 2010 +0530
@@ -1,11 +1,6 @@
 .. Objectives
 .. ----------
 
-.. A - Students and teachers from Science and engineering backgrounds
-   B - 
-   C - 
-   D - 
-
 .. Plotting a least square fit line
 
 .. Prerequisites
@@ -13,6 +8,7 @@
 
 ..   1. Basic Plotting
 ..   2. Arrays
+..   3. Loading data from files 
      
 .. Author              : Nishanth Amuluru
    Internal Reviewer   :