Vector Spaces - The Space F^n - Cooperstein Exercise 12, page 10

In summary, the conversation is about the book "Advanced Linear Algebra" by Bruce Cooperstein. The person is seeking help with Exercise 12 in Section 1.2, and has provided their attempted solution. However, the answer given by Cooperstein in the "Hints to Selected Problems" section is different from the person's solution, causing confusion. The person is asking for clarification and assistance in finding their error.
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I am reading Bruce Cooperstein's book: Advanced Linear Algebra ... ...

I am focused on Section 1.2 The Space \(\displaystyle \mathbb{F}^n\) ...

I need help with Exercise 12 ... since I do not get the same answer as the author ...

Exercise 12 reads as follows:

View attachment 5103My attempt at a solution to this apparently simple problem is as follows:
Let \(\displaystyle \underline{v} = \begin{pmatrix} v_1 \\ v_2 \end{pmatrix}\) ... ... We need to find \(\displaystyle v_1\) and \(\displaystyle v_2\) such that:

\(\displaystyle \begin{pmatrix} 2v_1 \\ 2v_2 \end{pmatrix} + \begin{pmatrix} 3 \\ 4 \end{pmatrix} = \begin{pmatrix} 1 \\ 3 \end{pmatrix}\) (mod 5) ... ... ... (1)Thus, given (1), we must have, for \(\displaystyle v_1\) :

\(\displaystyle 2 v_1 +3 = 1\) (mod 5)

so we must have

\(\displaystyle 2 v_1 = 1 - 3 = -2\) (mod 5)

and so

\(\displaystyle v_1 = -1 \equiv 4\) (mod 5)

----------------------------------------------

For \(\displaystyle v_2\), given (1)we must have

\(\displaystyle 2 v_2 + 4 = 3\) (mod 5)

So then we must have

\(\displaystyle 2 v_2 = 3 - 4 = -1 \equiv 4\) (mod 5)

and so

\(\displaystyle v_2 = 2\) Thus ...

\(\displaystyle \underline{v} = \begin{pmatrix} v_1 \\ v_2 \end{pmatrix} = \begin{pmatrix} 4 \\ 2 \end{pmatrix}\)BUT ... in the "Hints to Selected Problems, Cooperstein gives the answer as\(\displaystyle \underline{v} = \begin{pmatrix} v_1 \\ v_2 \end{pmatrix} = \begin{pmatrix} 3 \\ 4 \end{pmatrix}\)
So, my problem is ... why is there a discrepancy ... where is my error ...?

Hope someone can help ...

Peter
 
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  • #2
It looks as though the error is Cooperstein's, not yours.
 

FAQ: Vector Spaces - The Space F^n - Cooperstein Exercise 12, page 10

What is a vector space?

A vector space is a mathematical structure that consists of a set of objects called vectors, along with operations that allow for the addition and multiplication of vectors. The space is typically denoted as V, and the vectors are usually represented as n-tuples of numbers (F^n).

What is the Space F^n?

The Space F^n refers to the set of all n-tuples of numbers from the field F. In other words, it is the set of all possible combinations of n numbers from the field F. For example, if F is the set of real numbers, then F^n would include all possible lists of n real numbers.

What is Cooperstein Exercise 12?

Cooperstein Exercise 12 is a specific exercise in a mathematics textbook or course that focuses on vector spaces and the space F^n. It is named after the author or creator of the exercise, and it is likely designed to help students practice and understand concepts related to vector spaces.

What is the purpose of studying vector spaces?

The concept of vector spaces is fundamental in many areas of mathematics and science. It is used to describe and model a wide range of phenomena, from physical systems to abstract mathematical concepts. Studying vector spaces helps develop important skills in problem-solving and critical thinking, and it provides a foundation for more advanced topics in mathematics.

What are some examples of vector spaces?

Some examples of vector spaces include Euclidean space, which consists of all n-tuples of real numbers, and the space of polynomials, which consists of all possible polynomials with coefficients from a given field. Other examples include spaces of matrices, functions, and geometric objects such as lines and planes.

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