In these simple approximation schemes, the area above each subinterval is approximated by the area of a rectangle, with the height of the rectangle being chosen according to some rule. In particular, we will consider the following rules:

**left endpoint rule**-
The height of the rectangle is the value of
the function
*f*(*x*) at the left-hand endpoint of the subinterval. **right endpoint rule**-
The height of the rectangle is the value of
the function
*f*(*x*) at the right-hand endpoint of the subinterval. **midpoint rule**-
The height of the rectangle is the value of
the function
*f*(*x*) at the midpoint of the subinterval.

The Maple `student` package has commands for visualizing these
three rectangular area approximations. To use them, you first must
load the package via the `with` command. Then try the three
commands given below. Make sure you understand the differences between
the three different rectangular approximations. Take a moment to see
that the different rules choose rectangles which in each case will
either underestimate or overestimate the area. Even the midpoint
rule, whose rectangles usually have heights more appropriate than
those for the left endpoint and right endpoint rules, will produce an
approximation which is not exact.

> with(student):

> rightbox(x^2,x=0..4);

> leftbox(x^2,x=0..4);

> middlebox(x^2,x=0..4);

There are also Maple commands `leftsum`, `rightsum`, and `
middlesum` to sum the areas of the rectangles, see
the examples below. Note the use of `evalf` to obtain numerical answers.

> rightsum(x^2,x=0..4);

> evalf(rightsum(x^2,x=0..4));

> middlesum(x^2,x=0..4);

> evalf(middlesum(x^2,x=0..4));

The Maple commands above use the short-hand summation notation. Since there are only four terms in the sums above, it isn't hard to write them out explicitly, as follows.

However, if the number of terms in the sum is large, summation notation saves a lot of time and space.

It should be clear from the graphs that adding up the areas of the
rectangles only approximates the area under the curve. However, by
increasing the number of subintervals the accuracy of the
approximation can be increased. All of the Maple commands described so
far in this lab permit a third argument to specify the number of
subintervals. The default is 4 subintervals. See the example below
for the area under *y*=*x* from *x*=0 to *x*=2 using the `rightsum`
command with 4, 10, 20 and 100 subintervals. (As this region describes
a right triangle with height 2 and base 2, this area can be easily
calculated to be exactly 2.) Try it yourself with the `leftsum`
and `middlesum` commands.

> evalf(rightsum(x,x=0..2));

> evalf(rightsum(x,x=0..2,10));

> evalf(rightsum(x,x=0..2,20));

> evalf(rightsum(x,x=0..2,100));

Since, in this trivial example, we knew that the area is exactly 2, it appears that, as the number of subintervals increases, the rectangular approximation becomes more accurate. What would happen with a not so trivial region? The next two sections describe ways of assessing the accuracy of some rectangular approximations.

Tue Nov 5 14:24:02 EST 1996