In Exercises 21 and 22, mark each statement True or False. Justify each answer. 21. a. A single vector by itself is linearly dependent. b. If H = Span { b 1 ,…, b p }, then { b 1 ,…, b p } is a basis for H . c. The columns of an invertible n × n matrix form a basis for ℝ n . d. A basis is a spanning set that is as large as possible. e. In some cases, the linear dependence relations among the columns of a matrix can be affected by certain elementary row operations on the matrix.
In Exercises 21 and 22, mark each statement True or False. Justify each answer. 21. a. A single vector by itself is linearly dependent. b. If H = Span { b 1 ,…, b p }, then { b 1 ,…, b p } is a basis for H . c. The columns of an invertible n × n matrix form a basis for ℝ n . d. A basis is a spanning set that is as large as possible. e. In some cases, the linear dependence relations among the columns of a matrix can be affected by certain elementary row operations on the matrix.
In Exercises 21 and 22, mark each statement True or False. Justify each answer.
21. a. A single vector by itself is linearly dependent.
b. If H = Span {b1,…,bp}, then {b1,…,bp} is a basis for H.
c. The columns of an invertible n × n matrix form a basis for ℝn.
d. A basis is a spanning set that is as large as possible.
e. In some cases, the linear dependence relations among the columns of a matrix can be affected by certain elementary row operations on the matrix.
Quantities that have magnitude and direction but not position. Some examples of vectors are velocity, displacement, acceleration, and force. They are sometimes called Euclidean or spatial vectors.
Introductory and Intermediate Algebra for College Students (5th Edition)
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, algebra and related others by exploring similar questions and additional content below.