MATH 260

FINAL EXAM

 

1.        (8pts) Consider the planes given by the equations and . Find the equation of the line of intersection of these two planes.

2.        (18pts) Consider the points   and

a)       Find the vectors a= and b=.

b)       Compute ab and ab.

c)       What is the angle between a and b?

d)       Compute the vector projection of a on b.

e)       Find the all lines determined by these three points.

f)        Do these three point determine a plane?

3.        (15pts) Consider the function of two variables .

a)       Find all critical points and classify them as local max, local min, or saddle points.

b)       Find the absolute maximum and minimum of this function on the triangle with vertices (-4,4), (4,4) and (-4,-4).

 

4.        (10pts) Find the volume inside both the sphere  and the cylinder where . Check your answer.         

5.        (9pts) Consider the following matrix:. Find all eigenvalues of the matrix and for one of the eigenvalues, find a corresponding eigenvector.

6.        (10pts) Consider the following system of linear equations:

Write down all solutions to this system.

7.        (10pts) You wish to make a cylinder that will hold 2gallons of liquid. Find the radius and the height   

        of the cylinder that minimizes the amount of material to be used.

8.        (6pts) Determine if the vectors , and  are linearly independent in R. Do they form a basis for R?

9.        (9pts) Consider the function :

a)       Find the direction of greatest increase at the point (1,-1,-1).

b)       What is the directional derivative in this direction (i.e. what is the greatest increase)?

c)       Find the tangent plane to this surface at this point?

10.     (5pts) Let  be a function of three variables such that

and . Find .

11.     (Extra credit 10pts). Show that if three vectors in Rdo not all lie in the same plane, then they form a basis for  R.  Let A be an matrix with entries in R. If is an eigenvalue for A, show that all eigenvectors corresponding to form a subspace of R(this is called the eigenspace for .