All Calculus 1 Resources
Example Questions
Example Question #451 : Other Differential Functions
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
Trigonometric derivative:
Note that u may represent large functions, and not just individual variables!
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #1672 : Calculus
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
Derivative of an exponential:
Trigonometric derivative:
Note that u may represent large functions, and not just individual variables!
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #1673 : Calculus
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
Derivative of an exponential:
Trigonometric derivative:
Note that u and v may represent large functions, and not just individual variables!
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #1674 : Calculus
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
Trigonometric derivative:
Quotient rule:
Note that u and v may represent large functions, and not just individual variables!
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #451 : How To Find Differential Functions
Determine the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
Derivative of an exponential:
Trigonometric derivative:
Note that u may represent large functions, and not just individual variables!
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #1676 : Calculus
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
Derivative of an exponential:
Trigonometric derivative:
Note that u may represent large functions, and not just individual variables!
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #461 : Other Differential Functions
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #462 : Other Differential Functions
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #1679 : Calculus
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
Trigonometric derivative:
Note that u and v may represent large functions, and not just individual variables!
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
Example Question #463 : Other Differential Functions
Find the slope of the function at
.
To consider finding the slope, let's discuss the topic of the gradient.
For a function , the gradient is the sum of the derivatives with respect to each variable, multiplied by a directional vector:
It is essentially the slope of a multi-dimensional function at any given point
Knowledge of the following derivative rules will be necessary:
Derivative of a natural log:
Trigonometric derivative:
Note that u may represent large functions, and not just individual variables!
The approach to take with this problem is to simply take the derivatives one at a time. When deriving for one particular variable, treat the other variables as constant.
at
x:
y:
The slope is
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