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 | Invertible change of basis matrix | Linear Algebra | Khan Academy | 13:34 | 0 | 1 list |
 | Change of basis matrix | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy | 17:55 | 0 | 1 list |
 | Coordinates with respect to a basis | Linear Algebra | Khan Academy | 16:80 | 0 | 1 list |
 | Least squares examples | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy | 18:50 | 0 | 1 list |
 | Another least squares example | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy | 13:25 | 0 | 1 list |
 | Least squares approximation | Linear Algebra | Khan Academy | 15:32 | 0 | 1 list |
 | Projection is closest vector in subspace | Linear Algebra | Khan Academy | 9:50 | 0 | 1 list |
 | Another example of a projection matrix | Linear Algebra | Khan Academy | 21:36 | 0 | 1 list |
 | Subspace projection matrix example | Linear Algebra | Khan Academy | 13:40 | 0 | 1 list |
 | A projection onto a subspace is a linear transformation | Linear Algebra | Khan Academy | 16:16 | 0 | 1 list |
 | Visualizing a projection onto a plane | Linear Algebra | Khan Academy | 9:28 | 0 | 1 list |
 | Projections onto subspaces | Linear Algebra | Khan Academy | 17:26 | 0 | 1 list |
 | Showing that A-transpose x A is invertible | Matrix transformations | Linear Algebra | Khan Academy | 12:34 | 0 | 1 list |
 | Rowspace solution to Ax = b example | Linear Algebra | Khan Academy | 19:38 | 0 | 1 list |
 | Unique rowspace solution to Ax = b | Linear Algebra | Khan Academy | 19:12 | 0 | 1 list |
 | Orthogonal complement of the nullspace | Linear Algebra | Khan Academy | 3:27 | 0 | 1 list |
 | Orthogonal complement of the orthogonal complement | Linear Algebra | Khan Academy | 12:18 | 0 | 1 list |
 | Representing vectors in rn using subspace members | Linear Algebra | Khan Academy | 27:10 | 0 | 1 list |
 | Slope and Y-intercept Intuition | 5:54 | 0 | |
 | Basic Graphing and Coordinates | 12:30 | 0 | |
 | Area of a circle | 6:45 | 0 | |
 | Circles: radius, diameter, circumference and Pi | Geometry | Khan Academy | 11:50 | 0 | |
 | Area and Perimeter | 12:20 | 0 | |
 | dim(v) + dim(orthogonal complement of v) = n | Linear Algebra | Khan Academy | 9:27 | 0 | 1 list |
 | rank(a) = rank(transpose of a) | Matrix transformations | Linear Algebra | Khan Academy | 11:14 | 0 | |
 | Orthogonal complements | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy | 22:80 | 0 | |
 | Visualizations of left nullspace and rowspace | Linear Algebra | Khan Academy | 19:50 | 0 | |
 | Rowspace and left nullspace | Matrix transformations | Linear Algebra | Khan Academy | 23:19 | 0 | |
 | Alternate Solution to Ratio Problem (HD Version) | 7:20 | 0 | |
 | More advanced ratio problem--with Algebra (HD version) | 9:58 | 0 | |
 | Ratio problem with basic algebra (new HD) | 5:12 | 0 | |
 | Introduction to ratios | Ratios, proportions, units, and rates | Pre-Algebra | Khan Academy | 14:13 | 0 | |
 | Transpose of a vector | Matrix transformations | Linear Algebra | Khan Academy | 12:70 | 0 | |
 | Transposes of sums and inverses | Matrix transformations | Linear Algebra | Khan Academy | 8:41 | 0 | |
 | Determinant of transpose | Matrix transformations | Linear Algebra | Khan Academy | 14:10 | 0 | |
 | Transpose of a matrix product | Matrix transformations | Linear Algebra | Khan Academy | 8:50 | 0 | |
 | Transpose of a matrix | Matrix transformations | Linear Algebra | Khan Academy | 8:37 | 0 | |
 | Determinant as scaling factor | Matrix transformations | Linear Algebra | Khan Academy | 20:10 | 0 | |
 | Determinant and area of a parallelogram | Matrix transformations | Linear Algebra | Khan Academy | 21:38 | 0 | |
 | Simpler 4x4 determinant | Matrix transformations | Linear Algebra | Khan Academy | 9:13 | 0 | |
 | Upper triangular determinant | Matrix transformations | Linear Algebra | Khan Academy | 8:70 | 0 | |
 | Determinant after row operations | Matrix transformations | Linear Algebra | Khan Academy | 10:25 | 0 | |
 | Duplicate row determinant | Matrix transformations | Linear Algebra | Khan Academy | 8:19 | 0 | |
 | Determinant when row is added | Matrix transformations | Linear Algebra | Khan Academy | 16:55 | 0 | |
 | (correction) scalar multiplication of row | Matrix transformations | Linear Algebra | Khan Academy | 2:52 | 0 | |
 | Determinant when row multiplied by scalar | Matrix transformations | Linear Algebra | Khan Academy | 13:20 | 0 | |
 | Scientific notation examples | Pre-Algebra | Khan Academy | 12:49 | 0 | |
 | Rule of Sarrus of determinants | Matrix transformations | Linear Algebra | Khan Academy | 7:18 | 0 | |
 | Determinants along other rows/cols | Matrix transformations | Linear Algebra | Khan Academy | 9:30 | 0 | |
 | n x n determinant | Matrix transformations | Linear Algebra | Khan Academy | 18:40 | 0 | |
 | 3 x 3 determinant | Matrix transformations | Linear Algebra | Khan Academy | 10:10 | 0 | |
 | Introduction to scientific notation | Pre-Algebra | Khan Academy | 20:48 | 0 | |
 | Formula for 2x2 inverse | Matrix transformations | Linear Algebra | Khan Academy | 18:20 | 0 | |
 | Derivative as slope of a tangent line | Taking derivatives | Differential Calculus | Khan Academy | 15:43 | 0 | |
 | The derivative of f(x)=x^2 for any x | Taking derivatives | Differential Calculus | Khan Academy | 11:50 | 0 | |
 | Calculating slope of tangent line using derivative definition | Differential Calculus | Khan Academy | 8:28 | 0 | |
 | Example of finding matrix inverse | Matrix transformations | Linear Algebra | Khan Academy | 6:22 | 0 | |
 | Deriving a method for determining inverses | Matrix transformations | Linear Algebra | Khan Academy | 18:00 | 0 | |
 | Showing that inverses are linear | Matrix transformations | Linear Algebra | Khan Academy | 21:25 | 0 | |
 | Simplifying conditions for invertibility | Matrix transformations | Linear Algebra | Khan Academy | 6:37 | 0 | |
 | Matrix condition for one-to-one trans | Matrix transformations | Linear Algebra | Khan Academy | 20:00 | 0 | |
 | Exploring the solution set of Ax = b | Matrix transformations | Linear Algebra | Khan Academy | 16:34 | 0 | |
 | Simple Analysis of Cost per Job Saved from Stimulus | 3:10 | 0 | 1 list |
 | Determining whether a transformation is onto | Linear Algebra | Khan Academy | 25:51 | 65,713 | |
 | Relating invertibility to being onto and one-to-one | Linear Algebra | Khan Academy | 6:31 | 43,769 | |
 | Surjective (onto) and injective (one-to-one) functions | Linear Algebra | Khan Academy | 9:32 | 222,088 | |
 | Proof: Invertibility implies a unique solution to f(x)=y | Linear Algebra | Khan Academy | 22:41 | 35,088 | |
 | Introduction to the inverse of a function | Matrix transformations | Linear Algebra | Khan Academy | 18:54 | 108,862 | |
 | Distributive property of matrix products | Matrix transformations | Linear Algebra | Khan Academy | 9:52 | 20,553 | |
 | Matrix product associativity | Matrix transformations | Linear Algebra | Khan Academy | 11:59 | 19,891 | |
 | Matrix product examples | Matrix transformations | Linear Algebra | Khan Academy | 18:14 | 46,222 | |
 | Compositions of linear transformations 2 | Matrix transformations | Linear Algebra | Khan Academy | 16:31 | 30,989 | |
 | Compositions of linear transformations 1 | Matrix transformations | Linear Algebra | Khan Academy | 12:21 | 62,064 | |
 | FRB Commentary 3: Big Picture | 21:28 | 37,270 | 1 list |
 | FRB Commentary 2: Deposit Insurance | 17:20 | 34,093 | 1 list |
 | Fractional Reserve Banking Commentary 1 | 19:13 | 69,475 | 1 list |
 | Expressing a projection on to a line as a matrix vector prod | Linear Algebra | Khan Academy | 16:41 | 58,760 | |
 | Introduction to projections | Matrix transformations | Linear Algebra | Khan Academy | 14:37 | 133,317 | |
 | Unit vectors | Matrix transformations | Linear Algebra | Khan Academy | 6:59 | 118,643 | |
 | Rotation in R3 around the x-axis | Matrix transformations | Linear Algebra | Khan Academy | 12:18 | 76,113 | |
 | Linear transformation examples: Rotations in R2 | Linear Algebra | Khan Academy | 17:52 | 112,585 | |
 | Linear transformation examples: Scaling and reflections | Linear Algebra | Khan Academy | 15:13 | 119,343 | |
 | More on matrix addition and scalar multiplication | Linear Algebra | Khan Academy | 10:42 | 36,451 | |
 | Sums and scalar multiples of linear transformations | Linear Algebra | Khan Academy | 15:90 | 34,461 | |
 | Preimage and kernel example | Matrix transformations | Linear Algebra | Khan Academy | 15:23 | 98,275 | |
 | Preimage of a set | Matrix transformations | Linear Algebra | Khan Academy | 5:23 | 47,188 | |
 | (2^ln x)/x Antiderivative Example | 8:40 | 113,705 | |
 | im(T): Image of a transformation | Matrix transformations | Linear Algebra | Khan Academy | 16:37 | 99,368 | |
 | Image of a subset under a transformation | Matrix transformations | Linear Algebra | Khan Academy | 18:11 | 75,750 | |
 | Linear transformations as matrix vector products | Linear Algebra | Khan Academy | 17:32 | 196,587 | |
 | Matrix vector products as linear transformations | Linear Algebra | Khan Academy | 17:40 | 152,244 | |
 | Linear transformations | Matrix transformations | Linear Algebra | Khan Academy | 13:53 | 419,071 | |
 | Vector transformations | Matrix transformations | Linear Algebra | Khan Academy | 14:19 | 173,384 | |
 | A more formal understanding of functions | Matrix transformations | Linear Algebra | Khan Academy | 16:20 | 199,631 | |
 | Khan Academy on Facebook | 2:18 | 31,355 | |
 | Showing that the candidate basis does span C(A) | Vectors and spaces | Linear Algebra | Khan Academy | 13:40 | 31,756 | |
 | Showing relation between basis cols and pivot cols | Linear Algebra | Khan Academy | 8:33 | 41,736 | |
 | Dimension of the column space or rank | Vectors and spaces | Linear Algebra | Khan Academy | 12:48 | 160,734 | |
 | Dimension of the null space or nullity | Vectors and spaces | Linear Algebra | Khan Academy | 13:59 | 132,614 | |
 | Proof: Any subspace basis has same number of elements | Linear Algebra | Khan Academy | 21:35 | 44,430 | |
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