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A comprehensive guide to mathematical modeling, and computation techniques for solving complex problems in various fields, from engineering to finance.

This is an informal and human readable description of an algorithm leaving many granular details of it.

- Algorithm
- Instruction
- Process
**Pseudocode**

Only four points are needed in constructing a fourth order Newton Divided Difference polynomial,

- True
**False**

It is impossible to find the complex roots of a polynomial function, using Newton’s Method” is:

- True
**False**

Given a matrix A , its QR -decomposition is an upper triangular matrix and an orthogonal matrix. An orthogonal matrix is a matrix whose transpose is equivalent to its inverse.

**True**- False

A matrix which is denoted by a boldface lowercase letter and expressed as 1 x n matrix is

- row vector
- no correct answer
**column vector**- not a matrix

Eigenvalues are used in the analysis of linear transformation such as scaling.

**True**- False

If A is a 3 x 3 matrix and B is a 3x2 matrix , the statement “ A – B is not possible” is

**True**- False

The determinant of the given matrix is equal to |D| = 27.

**True**- False

Creating a mathematical model that will compute the following limit as will produce a result of

- 0
- indeterminate
- infinite
**1**

Suppose we do not know that the true value of the root of f(x) = x3 -1 is 1. How many iterations will be used to get the true value suppose the initial value of x = 0?

**2**- 4
- 1
- 3

Another condition that must be satisfied is that the diagonal elements are all nonzero for the Gauss-Seidel method to be used:

- True
- False

If matrix A is invertible such that A−1 = L−TL−1 then matrix A can be decomposed using Cholesky’s method.

**True**- False

The Cholesky factorization for the sample matrix given above is:

**True**- False

The point was added to the Simpson’s 1/3 Rule which gives a better approximation to the integral of the function.

- True
**False**

Using Newton’s interpolation, with data given below to compute for f(1.5) The second ordervalue is 1/3.

- True
**False**

Newton’s Method is ideal to function which is

- Both of "Differentiable also known as a “smooth” function" and "Containing multiple roots." are correct
**Both of "Differentiable also known as a “smooth” function" and "Transcendental or that which cannot be expressed in finite number of terms." are correct**- All of the answers correct
- "Differentiable also known as a “smooth” function" is correct

The Secant method is convergent for the function f(x) = 3x4 – x -3 whose initial values are present between x0 = 2 and x1 = 4

- True
**False**

The eigenvalues of A = are λ = 0 and λ = -3.

**True**- False

For the function f(x) = ex-2 the next approximated value of the root when x0 = -1 and x1 = 1 is x2 = 0.98626.

- True
**False**

Since matrices are used to represent properties of images, it follows that transformation of images may use eigenvalues and eigenvectors to do that.

**True**- False

Given the function f(x) = 0.75 + 1.1x, an exact value can be given instantly by Trapezoidal rule

**True**- False

Direct method for finding the eigenvalues is recommended since the calculation of zeros of a polynomial is numerically challenging if not unstable.

- True
**False**

If matrix is A is positive definite then a11 > 0.

**True**- False

The approximate integral of will give a value of 0.1786

**True**- False

The function f(x) = x3 -5 with initial guesses x0 and x1 would converge.

**True**- False

For an interval of 0 to 1, a subinterval with a size of 0.2 will give n = 5 described as 5 segment Trapezoidal rule.

**True**- False

Using Newton’s interpolation, with data given below to compute for f(1.5) The first order from x0 = 0 to x1 = 3 has a value of 4.8 which is similar to Lagrange.

- True
**False**

A square matrix is said to be diagonally dominant if for every row of the matrix, the magnitude of the diagonal entry in a row is less than or equal to the sum of the magnitudes of all the other (non-diagonal) entries in that row.

- True
**False**

In the analysis of algorithm, this refers to the number of steps to be taken in an algorithm.

- Space complexity
**Time complexity**- Process Complexity
- Step complexity

Rate of growth of errors are needed to be identified, especially when dealing with iterative methods as this might affect the solution in general.

**True**- False

Newton’s method is based on a truncated version of the Taylor series keeping only the first order terms.

**True**- False

For the given systems of linear equations, with initial values x1 =0; x2 =0; x3 = 0. The next iterative value of x1 using Gauss-Seidel Method is 1.3333.

**True**- False

Simpson’s 1/3 rule is an example of an open type numerical integration method

- True
**False**

If the magnitude of the diagonals is greater than the sum of the non-diagonals in the same row, then the matrix is not diagonally dominant.

- True
**False**

Methods that uses a single initial value or two initial values that do not necessarily brackets the root where Newton’s method is categorized are called

**Open method**- Iterative method
- Closed method
- Non-bracketing method

The inverse of A which is a 3 x 2 matrix is A -1 = 2 x 3 matrix.

- True
**False**

The given matrix above is a symmetric matrix.

**True**- False

Best-case is the maximum number of steps taken on any instance of size of a variable.

- True
**False**

From the two data points(2,5) and (6, 11), using Lagrange polynomial method, the polynomial is Li(x) = 1.5x +2.

**True**- False

Approximating calculations which involve infinite value, most often used in series notations and in calculus doesn't introduce errors.

- True
**False**

A matrix decomposition method that has an upper triangular matrix and an orthogonal matrix is referred to as the QR

**True**- False

The coefficients of the Newton's interpolating polynomial can also be expressed in terms of divided difference.

**True**- False

Which of the following is the first step in solving computational problems?

- Specification of an Algorithm
- Development of a model
**Problem definition**- Designing an Algorithm

Newton’s method also known as the Newton-Raphson iteration is that, suppose at point xi of the function, there is a tangent at that point. This point is assumed to be:

**the root of the function**- the lower limit of the interval
- the derivative of the function
- the upper limit of the interval

The coefficient a0 is also equal to f(x0) in the Newton’s interpolating polynomial.

**True**- False

In the analysis of algorithm, this refers to the volume of memory.

- In the analysis of algorithm, this refers to the volume of memory.
- Select one:
**Space complexity**- Time complexity
- Step complexity
- Process Complexity

For both the Trapezoidal and Simpson’s 1/3 rule , using more strips will give better approximation of the curve.

**True**- False

Secant method is usually the best option if the function doesn’t have an exact formula but just a pair of x and y values.

**True**- False

Using Lagrange interpolation, with data given below compute for f(1.5) the solution is f(1.5) = 4.8

**True**- False

One of the advantages of Newton’s method is that its converges fast even if the initial guess was poorly chosen

- True
**False**

In creating a computer algorithm one important factor that should be considered is that the user would be prompted the values that are needed in solving.

**True**- False

Just like the Newton-Raphson method, the initial guesses affect the convergence of the Secant method.

**True**- False

Using Newton’s interpolation, with data given below compute for f(1.5) The solution of Y(1.5)=4.8

**True**- False

The determinant of the given matrix is D = |-5|.

- True
**False**

The approximated root using the secant method lies within the two initial points which is used to project the secant line.

- True
**False**

A continuous function’s integral is approximated using either the trapezoidal or Simpson’s rule by translating the function into discrete form.

**True**- False

Which of the following shows A - B ?

- Question text

The slope of the secant line has nothing to do with the convergence of the Secant method.

- True
**False**

The factorization in Cholesky’s Method can be generated efficiently by recurrence relations.

**True**- False

For practical reasons, the absolute error is usually more meaningful than the relative error.

- True
**False**

The Average case occurs in linear search algorithmwhen item is the last element in the array.

- True
**False**

Using Newton’s interpolation, with data given below to compute for f(1.5)

- True
**False**

A Hermitian matrix (or self-adjoint matrix) is a complex square matrix that is equal to its own conjugate transpose and can be decomposed using Cholesky’s method.

**True**- False

The relative error is related to the approximate value rather than to the exact value because the true value may not be known.

**True**- False

If the interval of the function is given as 0 to pi, for n = 6 segments, each node or segments will be

**True**- False

While using two sets of points (x0,y0) and (x1,y1) a straight line is formed and could use the slope equation which follows that the first derivative can be approximated using the given values.

**True**- False

Among the many applications of matrices are used in statistics, economics, physics, and engineering.

**True**- False

For the given systems of linear equations, with initial values x1 =0; x2 =0; x3 = 0. The next iterative value of x2 using Gauss-Seidel Method is 1.5.

- True
**False**

From the two data points (1,4) and (3, 7), and (4,10) using Lagrange polynomial method, the polynomial is Li(x) = 0.5x2 -0.5x +2.

- True
**False**

Rearranging rows are prohibited when evaluating the matrix if it is diagonally dominant.

- True
**False**

Reducing the equidistant points improves the approximation of the function, f(x) by the polynomial, P.

- True
**False**

Numerical methods give more accurate results than analytic methods.

- True
**False**

Numerical integrations such as Trapezoidal and Simpson’s 1/3 rule should have intervals that are uniform.

**True**- False

There exists a minimization problem such that (i) assuming P = NP, there is no polynomial-time 1-approximation algorithm for the problem; and (ii) for any constant ǫ > 0, there is a polynomial-time (1 + ǫ)-approximation algorithm for the problem.

**True**- False

Horner’s method which is a method for finding roots of a polynomial equation f(x) =0 is almost similar to Newton’s method.

**True**- False

In numerical integration, when both the end points of the interval of integration are used as nodes in the methods, the methods are called closed type methods

**True**- False

An algorithm design technique is a general approach to solving problems algorithmically that is applicable to a variety of problems from different areas of computing.

**True**- False

In the analysis of algorithm, this is maximum number of steps taken on any instance of size a.

**worst-case**- best-case
- amortized
- average-case

Power method is an iterative approach that can be employed to determine the largest or dominant eigenvalue

**True**- False

The same algorithm can be represented in several different ways.

**True**- False

Choosing an initial guess which gives near f(x) = 0 is considered a good guess

**True**- False

The eigenvectors of A = and are the same.

- True
**False**

One of the advantages of secant method over the Newton’s Method is the use of derivatives.

**True**- False

The determinant of the given matrix is?

- 4
- 5
**No correct answer**- 2

Which of the following statements is true for the function f(x) = -e x + sin x, when 0 is used as an initial value:

- Newton’s method is divergent
- Newton’s method can be used since the function is “smooth”
- Newton’s method is convergent
- Newton’s method cannot be used

If A−1 (if it exists) the eigenvalues of A−1 is 1/5, ¼ and ½ if matrix A has eigenvalues 5, 4 and 2.

**True**- False

In numerical differentiation, using a very small step size may increase the approximation error.

**True**- False

In giving initial values of x0 and x1, both of them should preferably be close to the solution.

**True**- False

The commutative property also exist in matrices.

- True
**False**

First order differences is equivalent f[x0,x1] when i = 0.

**True**- False

What is the next approximated root for the function f(x) = ex + sin(x) when x0 = 0?

- -0.5
- 1
- Invalid initial value
- 0.5

Which of the following matrices can be represented by A = 5I? (where I is the identity matrix)

**[No Answer]**

Trapezoidal rule is a numerical method that approximates the value of a definite integral by using first degree polynomial

**True**- False

Another method called midpoint rule is an open type method numerical integration.

**True**- False

For the function f(x) = ex-2 the value of f(x2) when x0 = -1 and x1 = 1 is f(x) = -0.5248

**True**- False

An additional benefit of the power method is that the corresponding eigenvector is obtained as a by-product of the method.

**True**- False

Perform floating point addition of 3.1 x 10 -1 and 12.25 x 10 1. If only 3 significant figures are allowed for mantissa, determine the percent accuracy of the result.

- 99.88 %
- 89.72 %
**99.72 %**- 99.01 %

In the analysis of algorithm, this is the number of steps taken on any instance of size a.

**average-case**- worst-case
- amortized
- best-case

Which of the following shows A + B ?

- Question text

The goal in using Newton’s method is the When choosing an initial value, a good guess is : A value which when substituted to the function will give a near zero value A value with f ’(x) ≠ 0 Always starting with 0

- All of the answers correct
**"A value which when substituted to the function will give a near zero value" and "A value with f ’(x) ≠ 0" are correct.**- "A value which when substituted to the function will give a near zero value" is correct
- "A value which when substituted to the function will give a near zero value" and "Always starting with 0" are correct.

The iteration in Secant method may terminate if the difference between two successive approximations equal to zero.

**True**- False

In using smaller integration interval for multiple segments, Trapezoidal method can reduce the approximation error better than Simpson’s 1/3 rule

- True
**False**

If x2 is the approximated root in Secant method, it follows that; the value of f(x2) must be equal to 0.

**True**- False

The absolute error of the function f(x) = e x when the the true value of f(x) = 2.718281828 compared to the approximated value of using the first five terms of the Maclaurin Series center at when x = 1, c =0 is _____.

**9.95 x10-3**- 6.67 x10-3
- 8.83 x10-3
- 3.35 x10-3

Secant method replaces the tangent in Newton’s method to the slope of the function using two initial guesses.

**True**- False

In differentiation using numerical methods, one of the steps is interpolating the function by a polynomial p at suitable points.

**True**- False

In Newton-Cotes integration methods, the nodes are uniformly distributed in [a, b] with x0 = a, xn = band the spacing h = (b – a) / n.

**True**- False

Newton’s method is powerful in giving multiple roots of any differentiable function.

- True
- False

One of the advantages of using mathematical modeling is the ability to predict an output given a certain input.

**True**- False

Simpson's rule is a numerical method that approximates the value of a definite integral by using third degree polynomials

- True
**False**

For is the iteration may terminate if the difference between f (x) is already zero.

**True**- False

Secant method is categorized as bracketing method because it uses two points of the secant as initial values.

- True
**False**

The relative error is ______________ when the exact value is given by e = 2.718281828 and the approximate value is e a = 2.701.

- 7.55763 x 10-3
**6.35763 x 10-3**- 3.65763 x 10-3
- 5.65763 x 10-3

For the function , its first derivative is f’(x) is

- True
**False**

The degree of the polynomial for the 10 sample values or data points is equal to 10.

- True
**False**

Sequential algorithm is an algorithm which can be executed a piece at a time on many different processing devices, and then combined together again at the end to get the correct result.

- True
**False**

When the exact value is π = 3.14159265359 and the relative error is given as 0.001, the approximate value is ____________.

- 3.141706813
- 3.141890681
**3.141906813**- 3.141606813

The complexity of sorting algorithm measures the running time as a function of the number n of items to be sorter.

**True**- False

Which of the following is true about A - B?

- All of the answers correct.
- The resulting matrix A - B is a 3 x 2 matrix.
- A - B is the same as B - A.
**Subtraction of matrices is not possible.**

Which of the following statements about algorithm is INCORRECT?

- Algorithms must have a unique name
- Algorithms are well-ordered with unambiguous operations
**Algorithms can run for infinitely**- Algorithms should have explicitly defined set of inputs and outputs

Triangular matrices have their eigenvalues on the diagonal of the matrix therefore the eigenvalues of A are the diagonal elements.

**True**- False

This is defined as the high level descriptions of instruction which is intended for human reading.

- Algorithm
- Instruction
**Pseudocode**- Process

The value of is

**a negative value**- a positive value
- has an absolute value of less than 1
- zero

Matrix multiplication may proceed if the number of columns of the 1st matrix is equal to the number of rows of the 2nd one.

**True**- False

Algorithms should have explicitly defined set of inputs and outputs

**True**- False

Using Lagrange interpolation, with data given below compute for f(1.5)

**True**- False

The matrix defined as is an upper triangular matrix

- True
**False**

For a two segment trapezoidal rule, it will use the points similar to the ones used by Simpson’s 1/3 rule.

**True**- False

The Secant method is convergent for the function f(x) = 3x4 – x -3 whose initial values are present between x0 = 0 and x1 = -1

**True**- False

If matrix A gives the largest eigenvalue, it suggests that if A -1 exists, the smallest eigenvalue can be obtained through inverse power method.

**True**- False

Roots of transcendental functions are easily approximated using Newton’s method provided that f’(x) ≠ 0.

**True**- False

The tangent line is projected to approximate the root of the function where it crosses the

- y axis
- origin
- function at its lowest point
- x axis

The approximate value of f(x) = e x using the first five terms of the Maclaurin Series center at when x = 1, c =0 is

- 2.708
- 2.525
- 2.803
- 2.656

Which of the following is true about A x B?

- All of the answers correct.
**The resulting matrix A x B is a 3 x 2 matrix.**- Matrix multiplication is not possible.
- A x B is the same as B x A.

The eigenvalues of A = have no rational values because of the zero element in the matrix.

- True
**False**

Using Newton’s interpolation, with data given below to compute for f(1.5) The first order from x0 = 3 to x1 = 5 has a value of 1

**True**- False

If a matrix has its entire diagonal elements are positive, then the real parts of its eigenvalues are negative.

- True
**False**

In mathematical modeling, a physical system is translated into mathematical expressions in order to be implemented in computers.

- In mathematical modeling, a physical system is translated into mathematical expressions in order to be implemented in computers.
- Select one:
**True**- False

Using the Maclaurin series expansion of cos(x) , when x =

**True**- False

The approximate integral of

**True**- False

Positive definite matrix can be efficiently solved using Cholesky decomposition.

**True**- False

The part where the derivative of the Newton-Raphson was replaced by the slope of the secant line in Secant method.

**True**- False

A cubic polynomial can interpolate three points.

- True
**False**

In the case of the tridiagonal system strict diagonal dominance means simply that (with a0 = an = 0)

**True**- False

The goal in using Newton’s method is the When choosing an initial value, a good guess is :

- "A value which when substituted to the function will give a near zero value" is correct
**"A value which when substituted to the function will give a near zero value" and "A value with f ’(x) ≠ 0" are correct.**- "A value which when substituted to the function will give a near zero value" and "Always starting with 0" are correct.
- All of the answers correct

Suppose a computing machine can only display up to 4 decimal places. Assuming that the true value of π is 3.14159265359. Using an approximate value of πa = 3.1416 Calculate the absolute error and the relative error.

- ɛa = 7.28754 x 10-7, %ɛ = 2.2264 x 10 -6
- ɛa = 7.4132 x 10-7, %ɛ = 2.8243 x 10 -6
**ɛa = 7.346410 x 10-7, %ɛ = 2. 3384 x 10 -6**- ɛa = 7.1126 x 10-7, %ɛ = 2.8124 x 10 -6

When it comes to computer implementation, secant method may have disadvantage over the Newton-Raphson since Secant method depends on the previous approximation making it slower than the Newton Raphson

**True**- False

Which of the following is not true in finding the determinant of a matrix?

- No correct answer
- It doesn’t work with non-square matrix.
**The operation between the matrices also takes an alternate sign of negative first then positive.**- Coefficients from systems of linear equations may form a matrix and could be used for finding the determinant.

Newton’s method and secant method has almost the same concept and are both fast.

**True**- False

Thealgorithm of the Trapezoidalrule is described by

**True**- False

Matrix has repeated eigenvalues

**True**- False

The secant method can fail to find a root of a nonlinear function that has a small slope near the root assures the presence of the root.

- True
**False**

The elements of both the coefficient matrix and determinant are the same, and so is their the mathematical concept.

- True
**False**

The eigenvalues that corresponds to the characteristic polynomial are λ2-4λ+3 are λ = 1 and λ = -3.

- True
**False**

In employing Gauss-Seidel method, the most recent values should be used to substitute with the formula of finding x1, x2 and x3, respectively.

**True**- False

Gauss-Jordan method consists of guessing a value and then using a systematic method to obtain a refined estimate of the root.

**True**- False

In floating point addition, where the exponent of the smaller number must match that of the larger number making 3.141516 x 101 and 2.125 x 102 expressed in 3 digit precision as 0.314 x 102 and 2.13 x 102

**True**- False

The iteration may terminate if the difference between approximated values of x is already zero.

**True**- False

Each component of the new iterates in Gauss-Seidel method depends upon all previously computed components, the updates cannot be done simultaneously.

**True**- False

The largest eigenvalue of A−1 is the smallest eigenvalue of A in magnitude.

**True**- False

The characteristic polynomial formed from the matrix

**True**- False

If the function, f(x) = cos3x was approximated by the polynomial, P(1.5) = -0.2, the amount of error approximately 0.05

**True**- False

If QT is the transpose of Q then QT Q = I or the identity matrix.

**True**- False

For the function f(x) =its first derivative is f’(x) is The first derivative of the function is f’(x) =

- True
**False**

The determinant of an identity matrix is equal to

- -1
- 0
**1**- Infinite

In the analysis of algorithm, this is minimum number of steps taken on any instance of size a.

- worst-case
- amortized
**best-case**- average-case

A mathematical model that will compute the following limit as will readily give _____________ answer.

**indeterminate**- 0
- finite
- infinite

Interpreting the results graphically is one advantages of using software systems in numerical methods.

**True**- False

The absolute value of the ratio of is x0 = 0 is 8

**True**- False

Simpson’s 1/3 rule uses a second degree polynomial formed by the two points of the original function.

- True
**False**

It is possible to approximate a function by using values outside the data points which is known as the linear interpolation.

- True
**False**

If there is a randomized algorithm that solves a decision problem in time t and outputs the correct answer with probability 0.5, then there is a randomized algorithm for the problem that runs in time Θ(t) and outputs the correct answer with probability at least 0.99.

- True
**False**

To measure the efficiency of the algorithm, the space and time efficiency are the important factors

**True**- False

The essential features of a physical system or process in mathematical terms should be carried out in the formulation of a mathematical model.

**True**- False

Which of the following correctly describes an algorithm?

- All of these
- It is an efficient method that can be expressed within finite amount of time and space.
- An algorithm is a set of steps of operations to solve a problem performing calculation, data processing, and automated reasoning tasks.
- Algorithm is being used to determine the most practical kinds of solution to solve a problem.

In general, an n × n matrix will have a characteristic polynomial of degree of n+ 1, and its roots are the eigenvalues of A.

- True
**False**

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