doc: fix a few rst errors

doc/stdlib/base.rst

@@ -367,8 +367,8 @@ Generic Functions
    The elements generated by all the arguments are appended into a single
    list, which is then passed to ``f`` as its argument list.
 
-   **Example**:
-   	
+   **Example**::
+
    	# Define a function f
    	julia> function f(x, y)
    	           x + y
@@ -387,6 +387,7 @@ Generic Functions
    Determine whether the given generic function has a method matching the given tuple of argument types.
 
    **Example**::
+
    	julia> method_exists(length, (Array,))
    	true
 
@@ -498,6 +499,7 @@ The ``state`` object may be anything, and should be chosen appropriately for eac
    Return an iterator that yields ``(i, x)`` where ``i`` is an index starting at 1, and ``x`` is the ``ith`` value from the given iterator. It's useful when you need not only the values `x` over which you are iterating, but also the index `i` of the iterations.
 
    **Example**::
+
    	julia> a = ["a", "b", "c"]
    	julia> for (index, value) in enumerate(a)
                    println("$index $value")

doc/stdlib/linalg.rst

@@ -445,8 +445,9 @@ Linear algebra functions in Julia are largely implemented by calling functions f
 .. function:: linreg(x, y) -> [a; b]
 
    Linear Regression. Returns ``a`` and ``b`` such that ``a+b*x`` is the closest line to the given points ``(x,y)``. In other words, this function determines parameters ``[a, b]`` that minimize the squared error between ``y`` and ``a+b*x``. 
-   
+
    **Example**::
+
       using PyPlot;
       x = float([1:12])
       y = [5.5; 6.3; 7.6; 8.8; 10.9; 11.79; 13.48; 15.02; 17.77; 20.81; 22.0; 22.99]