Directional Derivatives and the Gradient
Rates of change in an arbitrary direction, packaged into the gradient vector — pointing where the function increases fastest, normal to level curves.
Active Calculus Multivariable, Directional Derivatives and the Gradient
6 exercises
Activity 11.8.2
In this activity, we will use equation to calculate and interpret directional derivatives for the function .
Activity 11.8.5
We will look algebraically calculating and explaining the vector properties of the gradient using the function at the input .
Calculate the gradient of
Calculate .
Calculate for each of the following vectors:
What direction will correspond to the greatest rate of increase for at the input ? Find the value of the directional derivative in this direction.
Activity 11.8.6
This activity considers directional derivatives and gradients for a function that measures elevation. Suppose you are hiking in a foggy park and can only see a few feet in front of you. There is nothing blocking you from walking in any particular direction, but because of the fog you cannot see where the highest point on the mountain is. You want to try to find the top of the mountain, but you don…
Exercise 24
Let represent the elevation on a land mass at location . Suppose that , , and are all measured in meters.
Find and .
Let be a unit vector in the direction of . Determine . What is the practical meaning of and what are its units?
Find the direction of greatest increase in at the point .
Find the instantaneous rate of change of in the direction of greatest decrease at the point . I…
Exercise 25
Find all directions in which the directional derivative of is 1 at the point .
Exercise 26
Find, if possible, a function such that . If not possible, explain why.
Adapted from Active Calculus Multivariable © 2013–2026 Nicholas Long, Mitchel T. Keller, and Steven Schlicker. Licensed under CC BY-SA 4.0. Source: Active Calculus Multivariable. Imported at revision 692c03c.