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Ch 3: Vectors in Linear Algebra

About This Chapter

The Vectors in Linear Algebra chapter of this Linear Algebra: Help & Tutorials course is the simplest way to master vectors in linear algebra. This chapter uses simple and fun videos that are about five minutes long, plus lesson quizzes and a chapter exam to ensure you learn the essentials of vectors in linear algebra.

Who's It For?

Anyone who needs help learning or mastering vectors in linear algebra will benefit from the lessons in this chapter. There is no faster or easier way to learn about vectors in linear algebra. Among those who would benefit are:

  • Students who have fallen behind in understanding working with vectors in linear algebra
  • Students who struggle with learning disabilities or learning differences, including autism and ADHD
  • Students who prefer multiple ways of learning math (visual or auditory)
  • Students who have missed class time and need to catch up
  • Students who need an efficient way to learn about vectors in linear algebra
  • Students who struggle to understand their teachers
  • Students who attend schools without extra math learning resources

How It Works:

  • Find videos in our course that cover what you need to learn or review.
  • Press play and watch the video lesson.
  • Refer to the video transcripts to reinforce your learning.
  • Test your understanding of each lesson with short quizzes.
  • Verify you're ready by completing the Vectors in Linear Algebra chapter exam.

Why It Works:

  • Study Efficiently: Skip what you know, review what you don't.
  • Retain What You Learn: Engaging animations and real-life examples make topics easy to grasp.
  • Be Ready on Test Day: Use the Vectors in Linear Algebra chapter exam to be prepared.
  • Get Extra Support: Ask our subject-matter experts any vectors in linear algebra question. They're here to help!
  • Study With Flexibility: Watch videos on any web-ready device.

Students Will Review:

This chapter helps students review the concepts in a vectors in linear algebra unit of a standard college algebra course. Topics covered include:

  • Discovering the basis of a vector space
  • Understanding linear combinations and span
  • Working with linear dependence & independence
  • The Gram-Schmidt Process
  • Orthonormal bases

9 Lessons in Chapter 3: Vectors in Linear Algebra
Test your knowledge with a 30-question chapter practice test
Scalars and Vectors: Definition and Difference

1. Scalars and Vectors: Definition and Difference

In this lesson, we will examine scalars and vectors, learn why it is important to know the difference between the two and why remembering to add a direction to many of your exam answers could be the reason you get it right or wrong.

Performing Operations on Vectors in the Plane

2. Performing Operations on Vectors in the Plane

After watching this video lesson, you should be able to add, subtract, and multiply your vectors. Learn how easy it is to perform these operations and what you need to keep in mind when performing these operations.

The Dot Product of Vectors: Definition & Application

3. The Dot Product of Vectors: Definition & Application

After watching this video lesson, you will be able to find the dot product of vectors both algebraically and geometrically. Learn the difference between the two and what you need in order to calculate them.

Vector Spaces: Definition & Example

4. Vector Spaces: Definition & Example

In this lesson, we'll discuss the definition and provide some common examples of vector spaces. We'll go over set theory, the axioms for vector spaces, and examples of axioms using vector spaces of the real numbers over a field of real numbers.

Finding the Basis of a Vector Space

5. Finding the Basis of a Vector Space

In this lesson we'll start by reviewing matrix reduced row echelon form, which is integral to finding a basis of a vector space. Then we'll work through a problem together to see exactly how finding a basis is accomplished.

Orthonormal Bases: Definition & Example

6. Orthonormal Bases: Definition & Example

In this lesson we show how independent vectors in a space can become a basis for the space and how this basis can be turned into an orthonormal basis. Having an orthonormal basis is useful in many applications involving vectors.

The Gram-Schmidt Process for Orthonormalizing Vectors

7. The Gram-Schmidt Process for Orthonormalizing Vectors

Linearly combining things is something we do quite naturally. When the things are vectors, there is a fantastic way to organize the vectors before combining them. In this lesson, we'll show how to orthonormalize vectors using the Gram-Schmidt process.

Linear Combinations & Span: Definition & Equation

8. Linear Combinations & Span: Definition & Equation

This lesson will cover the definitions of linear combinations and spans in terms of vector spaces, using a real world example and then a mathematical example. You will learn the official definitions and how to apply them in mathematics.

Linear Dependence & Independence: Definition & Examples

9. Linear Dependence & Independence: Definition & Examples

Linear dependence and independence are based on whether or not there is more than one solution to a system of equations. In this lesson, we'll look at how you can determine whether or not a system is independent and work through some examples.

Chapter Practice Exam
Test your knowledge of this chapter with a 30 question practice chapter exam.
Not Taken
Practice Final Exam
Test your knowledge of the entire course with a 50 question practice final exam.
Not Taken

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