

Critical points occur where the gradient is zero. This is guaranteed whenever

and either

or

.
The Hessian matrix for this function looks like

and has determinant

Maxima occur whenever the determinant is positive and

. Minima occur whenever both the determinant and

are positive. Saddle points occur whenever the determinant is negative.
At

, you have a saddle point since the determinant reduces to -324, so

is the saddle point.
At

, the determinant is

and

, so

is a local maximum.
No other critical points remain, so you're done.
Answer:
i think i am not sure
i am soo sorry if i gave it wrong but i think its A
Step-by-step explanation:
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Answer:

Step-by-step explanation:
<em>See comment for complete question.</em>
The given information is represented in the attached figure.
First convert 22°8'6'' and 30° 40’ 30” to degrees




Considering Jason's position:

Where x = distance between the tree and Alison
Make H the subject

Considering Alison's position

Make H the subject




Open bracket


Collect Like Terms



Make x the subject


Substitute 104.76 for x in 



The above represents the height of the tree.
The height of the owl is:


