All Calculus 1 Resources
Example Questions
Example Question #1501 : Calculus
Find the slope of the function at point
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 rule will be necessary:
Derivative of an exponential:
Note that 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.
Take the partial derivative of at point
:
:
The slope is
Example Question #292 : How To Find Differential Functions
Find the slope of the function at the point
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 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.
Take the partial derivatives of at the point
:
:
The slope is
Example Question #472 : Functions
Find the slope of the function at point
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 rule will be necessary:
Derivative of an exponential:
Note that 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.
Take the partial derivative of at point
:
:
:
The slope is
Example Question #481 : Differential Functions
Find the slope of the function at point
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:
Product rule:
Note that 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.
Take the partial derivatives of at point
:
:
:
The slope is
Example Question #295 : How To Find Differential Functions
Find the slope of the function at the point
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 rule will be necessary:
Derivative of an exponential:
Note that 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.
Take the partial derivative of at the point
:
:
The slope is
Example Question #296 : How To Find Differential Functions
What is the slope of the function at the point ?
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 rule will be necessary:
Derivative of an exponential:
Note that 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.
Find the partial derivatives of the function at the point
:
:
The slope is
Example Question #297 : How To Find Differential Functions
Calculate the slope of the function at the point
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 rule will be necessary:
Derivative of an exponentials:
Note that 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.
Find the partial derivatives of at the point
:
:
The slope is
Example Question #298 : How To Find Differential Functions
Find the slope of the function at the point
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:
Derivative of a natural log:
Note that 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.
Find the partial derivatives of at the point
:
:
The slope is
Example Question #481 : Functions
What is the slope of the line normal to the function at the point ?
The first step to finding the slope of the line normal to a point is to find the slope of the tangent at this point.
The slope of this tangent, in turn, is found by finding the value of the derivative of the function at this point.
Evaluating the function at the point
The slope of the tangent is
The slope of the normal line is the negative reciprocal of this value. Thus for this problem the normal is
Example Question #292 : Other Differential Functions
What is the slope of the line normal to the function at the point ?
The first step to finding the slope of the line normal to a point is to find the slope of the tangent at this point.
The slope of this tangent, in turn, is found by finding the value of the derivative of the function at this point.
Evaluating the function at the point
The slope of the tangent is
The slope of the normal line is the negative reciprocal of this value. Thus for this problem the normal is
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