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11 Cards in this Set
- Front
- Back
linear combination geometrically |
many vectors multiplied by many constants added together from tail to head |
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linear (in)dependence geometrically |
linear dependence- multiples of eachother (point in the same direction) |
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vector span |
set of all scalar multiples of the vector (set of all linear combinations of said vectors)
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subspace |
flat surface within R^n , an infinite subset of vectors from a larger space that satisfies properties of the larger space |
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dimension of a subspace |
the minimum number of vectors it takes to span the space
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hyperplane |
subspace that has 1 dimension less than its ambient space (in 3D space, hyperplane would be 2D), cuts the ambient space in half (one above one below)
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basic vectors |
group of vectors make a basis for a space (or subspace) if they are linearly independent and span the space
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coordinates in different bases |
coefficients alpha1 and alpha2 |
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(generic) factor analysis |
method to analyze data and see relationships as well as data reduction |
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loadings |
entries within the Factor vectors, give measure of significance for each variable to that factor |
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scores/coordinates |
entries in the coordinate matrix, give us idea of how important each factor is to each observation |