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What is the rank of the matrix formed by the vectors [1, 2, 3], [2, 4, 6], and [1, 0, 1]?
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What happens when two vectors in a set are scalar multiples of each other?
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Which Python function helps determine whether a set of vectors is linearly independent using rank?
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Which of the following sets of vectors is linearly dependent?
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---------- function of Attitude is prominent in case of stylish/

noticeable consumption objects (For example, Allen Solly, Louis Phillips, Peter

England etc.)

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If a vector in a set can be expressed as a linear combination of the others, the set is said to be:
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Consider vectors v₁ = [1, 2, 3] and v₂ = [2, 4, 6]. Which statement is true?
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A set of 3 vectors in ℝ³ will be linearly independent only if:
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“Consumer

behaviour gets affected based on where the shop assistant stands (far away or

too close).

This element of store

atmospherics that impacts consumer behaviour is known as

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Task 2: Python Implementation

Write a Python function using NumPy to check whether a given set of vectors is linearly independent or not. Use matrix rank for your logic.

Instructions:

  1. Define three vectors:

v1 = np.array([1, 2, 3])  

v2 = np.array([2, 4, 6])  

v3 = np.array([1, 0, 1])  

  1. Stack the vectors into a matrix.

  2. Use np.linalg.matrix_rank() to check independence.

Return whether the set is independent or dependent.

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