1. Clicker Question 1 What is ? A. x tan(x2) + C
B. ½ (sec(x2) + tan(x2)) + C
C. ln |sec(x2) + tan(x2)| + C
D. ½ tan(x2) + C
E. ½ ln |sec(x2) + tan(x2)| + C

2. Clicker Question 2 What is ? A. x2 tan(x) + C
B. x tan(x) + sec2(x) + C
C. x tan(x) – ln |sec(x)| + C
D. ½ x2 tan(x) + C
E. x tan(x) + ln |sec(x)| + C

3. Numerical (or Approximate) Integration (2/14/14)
To evaluate a definite integral, we always hope to apply the Fundamental Theorem by finding an antiderivative and then evaluating it at the endpoints. But this isn’t always possible or practical.
Another option always available is to do numerical integration to approximate the answer. Here we use Riemann sums.

4. Getting Good Approximations
In general, the more data you use (i.e., the more rectangles you measure), the better the estimate.
Methods (in increasing order of accuracy for a fixed number of rectangles)
Left or right-hand endpoints
Trapezoid Rule (average of the above)
Midpoint Rule
Simpson’s Rule

5. Simpson’s Rule
It turns out that the Midpoint Rule is about twice as accurate as the Trapezoid Rule and the errors are in opposite directions.
Hence we form a “weighted average”: Simpson’s Rule = (2 Midpoint + Trapezoid) / 3
Simpson’s Rule is in general extremely accurate even for small n (i.e., few rectangles).
Can get Simpson directly from the data using ( … ) / 6

6. Clicker Question 3
Suppose a definite integral has the following estimates for 10 subdivisions of the interval: Left-hand sum: 12.5 Right-hand sum: 16.5 Midpoint Rule sum: 13.0 What is the Simpson’s Rule estimate?
A B C D E

7. Assignment for Monday Finish up Hand-in #2 (due Monday in class)
Section 7.7 goes into much more detail on approximate integration than we need to, and defines Simpson’s Rule slightly differently, so just work from our notes please.
Do Exercise 3 on page 516 (note: no known way to use FTC on this one), but also compute the Simpson’s Rule estimate with n = 4 (i.e., use 9 data points) both using the weighted average of Trap and Mid and the ( ) / 6 method.