Calculus: Early Transcendentals
Calculus: Early Transcendentals
8th Edition
ISBN: 9781285741550
Author: James Stewart
Publisher: Cengage Learning
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### Linear Transformations and Independence

**Question 4:**  
If \( T : \mathbb{R}^n \to \mathbb{R}^m \) is a linear transformation, then \( T(\theta_n) = \theta_m \).

- True
- False

**Question 5: Independence**  
Every subset of a linearly independent set is linearly independent.

- True
- False

---

**Explanation:**

- **Linear Transformations:** A function \( T \) is a linear transformation if it satisfies the properties of additivity and homogeneity. In the case where \( \theta_n \) and \( \theta_m \) are the zero vectors in \( \mathbb{R}^n \) and \( \mathbb{R}^m \) respectively, the statement \( T(\theta_n) = \theta_m \) must hold true because linear transformations map the zero vector to the zero vector.

- **Linearly Independent Sets:** A set of vectors is linearly independent if no vector in the set can be written as a combination of the other vectors. From this definition, any subset of a linearly independent set will also be linearly independent, as removing vectors cannot introduce a linear dependence.
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Transcribed Image Text:### Linear Transformations and Independence **Question 4:** If \( T : \mathbb{R}^n \to \mathbb{R}^m \) is a linear transformation, then \( T(\theta_n) = \theta_m \). - True - False **Question 5: Independence** Every subset of a linearly independent set is linearly independent. - True - False --- **Explanation:** - **Linear Transformations:** A function \( T \) is a linear transformation if it satisfies the properties of additivity and homogeneity. In the case where \( \theta_n \) and \( \theta_m \) are the zero vectors in \( \mathbb{R}^n \) and \( \mathbb{R}^m \) respectively, the statement \( T(\theta_n) = \theta_m \) must hold true because linear transformations map the zero vector to the zero vector. - **Linearly Independent Sets:** A set of vectors is linearly independent if no vector in the set can be written as a combination of the other vectors. From this definition, any subset of a linearly independent set will also be linearly independent, as removing vectors cannot introduce a linear dependence.
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