Show that ||x|| is a norm on R^n

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SUMMARY

The discussion focuses on proving that the function ||x|| = √(x · x) is a norm on ℝⁿ. The proof demonstrates three key properties: (1) ||x|| = 0 if and only if x = 0, (2) ||cx|| = |c| ||x|| for any scalar c in ℝ, and (3) the triangle inequality ||x + y|| ≤ ||x|| + ||y||, which is supported by the Cauchy-Schwarz Inequality. The proof is structured logically and adheres to the definitions of a norm in vector spaces.

PREREQUISITES
  • Understanding of vector spaces in ℝⁿ
  • Familiarity with the concept of norms
  • Knowledge of the Cauchy-Schwarz Inequality
  • Basic proficiency in mathematical proofs
NEXT STEPS
  • Study the properties of norms in vector spaces
  • Learn about the Cauchy-Schwarz Inequality in detail
  • Explore other types of norms, such as the L1 and L∞ norms
  • Investigate applications of norms in functional analysis
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Mathematics students, educators, and anyone interested in linear algebra and functional analysis will benefit from this discussion, particularly those studying vector norms and their properties.

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Homework Statement


Show ||x|| = \sqrt{x \cdot x} is a norm on \mathbb{R}^n.


Homework Equations


Prop. 1. ||x|| = 0 IFF x=0.
2. \forall c \in \mathbb{R} ||cx|| = |c| \, ||x||.
3. ||x+y|| \leq ||x|| + ||y||.

Cauchy-Schwarz Inequality.


The Attempt at a Solution



Just want to check if I am showing this correctly. Note that I am using x in place of \vec{x} \in \mathbb{R}^n.

Let x \in \mathbb{R}^n. Suppose that ||x|| = \sqrt{x \cdot x}.

1. Suppose first that ||x||=0. Then 0 = \sqrt{x \cdot x} imples x \cdot x = 0. But x \cdot x = x_1^2 + \cdots + x_2^2 = 0 if and only if x_i =0 \forall x_i. Thus if ||x|| =0, then x=0. Suppose next that x=0. Then ||0|| = \sqrt{0^2 + \cdots + 0^2} = 0. Therefore if x=0, then ||x||=0.

2. Let c \in \mathbb{R}. Then ||cx|| = \sqrt{(cx_1)^2 + \cdots + (cx_n)^2} = c ||x||.

3. This follows from the Cauchy-Schwarz inequality which I have proven and will not show here.
 
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Everything looks correct.
 

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