All Linear Algebra Resources
Example Questions
Example Question #8 : Non Homogeneous Cases
Example Question #9 : Non Homogeneous Cases
Example Question #10 : Non Homogeneous Cases
Example Question #101 : Linear Equations
Example Question #102 : Linear Equations
Example Question #103 : Linear Equations
It is recommended that you use a calculator with matrix arithmetic capability for this question.
The graph of a quartic (degree four) polynomial passes through the following five points:
, , , ,
What is the cubic term of ?
Round to four decimal digits.
None of the other choices gives the correct response.
A quartic polynomial takes the form
where the are the coefficients. The value we are trying to identify is , the quartic term.
An equation can be formed from each given ordered pair by substituting the abscissa for and the ordinate for . The problem can be simplified somewhat by noting that, since the -intercept of the graph of is given as , . Therefore, we are looking for the coefficients of
.
The equations formed from the other four points are
Adding two to both sides of each equation:
This is a system of four linear equations in four variables, which can be rewritten as the matrix multiplication equation , where is the matrix of coefficients, , the column matrix of variables, and the matrix of constants; this equation is
We are trying to calculate ; since , , or
This calculates to
.
Since the cubic term is requested, select . The correct response is .
Example Question #103 : Linear Equations
The initial tableau for a system of linear inequalities being solved using the simplex method is
The variables are .
What is represented by the first row?
The objective function to be minimized,
The constraint
The constraint
The objective function to be maximized,
The constraint
The bottom row of an initial simplex tableau is the one that represents the objective function to be minimized; the other rows represent constraints on the variables in the system. In a system of three variables, the first three entries of one of the rows represent the coefficients of those variables; the next three represent those of slack variables introduced into the system, which were not part of the original inequality. The last entry gives the number the linear expression is less than or equal to. Therefore, the first row represents the inequality
,
which is a constraint of the system.
Example Question #104 : Linear Equations
The initial tableau for a system of linear inequalities being solved using the simplex method is
The variables are .
Which of the following is the objective function of the system?
The objective function cannot be determined by inspecting the initial tableau.
The objective function in a simplex method - the function to be minimized - is represented by the bottom row of the initial tableau, with the coefficients the additive inverses of the entries in that row. The objective function of the system is therefore .
Example Question #106 : Linear Equations
Write the initial simplex method tableau for the problem of maximizing the expression
subject to the constraints:
When writing the initial simplex method tableau for a system of linear inequalities, first, recast each inequality as an equation by introducing three other variables, , called slack variables, as follows:
becomes
becomes
becomes
The system of three inequalities in three equations becomes a system of three equations in six variables. The coefficients form the first three rows of the augmented matrix that sets up the initial simplex tableau.
The bottom row comprises the additive inverses of the coefficients of the expression to be maximized, or the objective function.
The initial tableau is therefore
.
Example Question #107 : Linear Equations
Given a minimization linear programming problem, the objective function of its dual maximization problem is .
True or false: It follows that in the original minimization problem, the objective function is .
False
True
False
The statement is false. To show the reason for this, let the original minimization problem be as follows - and note that the objective function has three variables, so there will be three linear constraints other than the trivial ones:
Minimize subject to:
To find the dual maximization problem:
First, form the matrix of coefficients of the constraints (other than the positivity constraints) and the objective function, with the objective function on the bottom:
Next, transpose the matrix:
This is the coefficient matrix of the dual maximization problem. The bottom row represents the coefficients of the objective function. This function is given to be , so
.
The coefficient matrix of the original problem is
Since the entries in the bottom row are still unknown, no information about the objective function of the original minimization problem has been revealed.