Online courses directory (210)

Conditional statements and deductive reasoning. Conditional statements exercise examples. Logical argument and deductive reasoning exercise example. Conditional statements and deductive reasoning. Conditional statements exercise examples. Logical argument and deductive reasoning exercise example.

A broad set of tutorials covering perimeter area and volume with and without algebra. Perimeter and Area Basics. Area and Perimeter. Perimeter of a Polygon. Perimeter of a shape. Perimeter 1. Finding dimensions given perimeter. Area 1. Finding dimensions given area. Perimeter and Area Basics. Triangle Area Proofs. Area of triangles. Interesting Perimeter and Area Problems. Area of Diagonal Generated Triangles of Rectangle are Equal. Area of an equilateral triangle. Area of shaded region made from equilateral triangles. Shaded areas. Challenging Perimeter Problem. Triangle inqequality theorem. Triangle inequality theorem. Koch Snowflake Fractal. Area of an equilateral triangle. Area of Koch Snowflake (part 1) - Advanced. Area of Koch Snowflake (part 2) - Advanced. Heron's Formula. Heron's formula. Part 1 of Proof of Heron's Formula. Part 2 of the Proof of Heron's Formula. Circles: Radius, Diameter and Circumference. Parts of a Circle. Radius diameter and circumference. Area of a Circle. Area of a circle. Quadrilateral Overview. Quadrilateral Properties. Area of a Parallelogram. Area of parallelograms. Area of a trapezoid. Area of a kite. Area of trapezoids, rhombi, and kites. Perimeter of a Polygon. Perimeter and Area of a Non-Standard Polygon. How we measure volume. Measuring volume with unit cubes. Volume with unit cubes. Measuring volume as area times length. Volume of a rectangular prism or box examples. Volume 1. Volume word problem example. Volume word problems. Solid Geometry Volume. Cylinder Volume and Surface Area. Volume of a Sphere. Solid geometry. Perimeter and Area Basics. Area and Perimeter. Perimeter of a Polygon. Perimeter of a shape. Perimeter 1. Finding dimensions given perimeter. Area 1. Finding dimensions given area. Perimeter and Area Basics. Triangle Area Proofs. Area of triangles. Interesting Perimeter and Area Problems. Area of Diagonal Generated Triangles of Rectangle are Equal. Area of an equilateral triangle. Area of shaded region made from equilateral triangles. Shaded areas. Challenging Perimeter Problem. Triangle inqequality theorem. Triangle inequality theorem. Koch Snowflake Fractal. Area of an equilateral triangle. Area of Koch Snowflake (part 1) - Advanced. Area of Koch Snowflake (part 2) - Advanced. Heron's Formula. Heron's formula. Part 1 of Proof of Heron's Formula. Part 2 of the Proof of Heron's Formula. Circles: Radius, Diameter and Circumference. Parts of a Circle. Radius diameter and circumference. Area of a Circle. Area of a circle. Quadrilateral Overview. Quadrilateral Properties. Area of a Parallelogram. Area of parallelograms. Area of a trapezoid. Area of a kite. Area of trapezoids, rhombi, and kites. Perimeter of a Polygon. Perimeter and Area of a Non-Standard Polygon. How we measure volume. Measuring volume with unit cubes. Volume with unit cubes. Measuring volume as area times length. Volume of a rectangular prism or box examples. Volume 1. Volume word problem example. Volume word problems. Solid Geometry Volume. Cylinder Volume and Surface Area. Volume of a Sphere. Solid geometry.

This topic introduces the basic conceptual tools that underpin our journey through Euclidean geometry. These include the ideas of points, lines, line segments, rays, and planes. Euclid as the Father of Geometry. Language and Notation of Basic Geometry. Lines, Line Segments, and Rays. Recognizing rays lines and line segments. Specifying planes in three dimensions. Points, lines, and planes. Language and Notation of the Circle. The Golden Ratio. Identifying Rays. Measuring segments. Measuring segments. Congruent segments. Congruent segments. Segment addition. Segment addition. Algebraic midpoint of a segment exercise. Midpoint of a segment. Euclid as the Father of Geometry. Language and Notation of Basic Geometry. Lines, Line Segments, and Rays. Recognizing rays lines and line segments. Specifying planes in three dimensions. Points, lines, and planes. Language and Notation of the Circle. The Golden Ratio. Identifying Rays. Measuring segments. Measuring segments. Congruent segments. Congruent segments. Segment addition. Segment addition. Algebraic midpoint of a segment exercise. Midpoint of a segment.

Identifying types of quadrilaterals, finding measurements, and applying and proving postulates. Quadrilateral Overview. Quadrilateral Properties. Area of a Parallelogram. Area of a Regular Hexagon. Sum of Interior Angles of a Polygon. Sum of the exterior angles of convex polygon. Proof - Opposite Angles of Parallelogram Congruent. Proof - Opposite Sides of Parallelogram Congruent. Proof - Diagonals of a Parallelogram Bisect Each Other. Rhombus Diagonals. Proof - Rhombus Diagonals are Perpendicular Bisectors. Proof - Rhombus Area Half Product of Diagonal Length. Area of a Parallelogram. Area of a Regular Hexagon. Problem involving angle derived from square and circle. 2003 AIME II Problem 7. CA Geometry: Deducing Angle Measures.

Not all things with four sides have to be squares or rectangles! We will now broaden our understanding of quadrilaterals!. Quadrilateral Overview. Quadrilateral Properties. Proof - Opposite Sides of Parallelogram Congruent. Proof - Diagonals of a Parallelogram Bisect Each Other. Proof - Opposite Angles of Parallelogram Congruent. Proof - Rhombus Diagonals are Perpendicular Bisectors. Proof - Rhombus Area Half Product of Diagonal Length. Area of a Parallelogram. Whether a Special Quadrilateral Can Exist. Rhombus Diagonals. Quadrilateral Overview. Quadrilateral Properties. Proof - Opposite Sides of Parallelogram Congruent. Proof - Diagonals of a Parallelogram Bisect Each Other. Proof - Opposite Angles of Parallelogram Congruent. Proof - Rhombus Diagonals are Perpendicular Bisectors. Proof - Rhombus Area Half Product of Diagonal Length. Area of a Parallelogram. Whether a Special Quadrilateral Can Exist. Rhombus Diagonals.

Triangles are not always right (although they are never wrong), but when they are it opens up an exciting world of possibilities. Not only are right triangles cool in their own right (pun intended), they are the basis of very important ideas in analytic geometry (the distance between two points in space) and trigonometry. Pythagorean Theorem. The Pythagorean theorem intro. Pythagorean Theorem 1. Pythagorean Theorem 2. Pythagorean Theorem 3. Pythagorean theorem. Introduction to the Pythagorean Theorem. Pythagorean Theorem II. Garfield's proof of the Pythagorean Theorem. Bhaskara's proof of Pythagorean Theorem. Pythagorean Theorem Proof Using Similarity. Another Pythagorean Theorem Proof. 30-60-90 Triangle Side Ratios Proof. 45-45-90 Triangle Side Ratios. 30-60-90 Triangle Example Problem. Special right triangles. Area of a Regular Hexagon. 45-45-90 Triangles. Intro to 30-60-90 Triangles. 30-60-90 Triangles II. Pythagorean Theorem. The Pythagorean theorem intro. Pythagorean Theorem 1. Pythagorean Theorem 2. Pythagorean Theorem 3. Pythagorean theorem. Introduction to the Pythagorean Theorem. Pythagorean Theorem II. Garfield's proof of the Pythagorean Theorem. Bhaskara's proof of Pythagorean Theorem. Pythagorean Theorem Proof Using Similarity. Another Pythagorean Theorem Proof. 30-60-90 Triangle Side Ratios Proof. 45-45-90 Triangle Side Ratios. 30-60-90 Triangle Example Problem. Special right triangles. Area of a Regular Hexagon. 45-45-90 Triangles. Intro to 30-60-90 Triangles. 30-60-90 Triangles II.

Similar Triangle Basics. Similarity Postulates. Similar triangles 1. Similar Triangle Example Problems. Similar triangles 2. Similarity Example Problems. Solving similar triangles 1. Similarity example where same side plays different roles. Challenging Similarity Problem. Finding Area Using Similarity and Congruence. Similar triangles. Similar triangles (part 2). Similar Triangle Basics. Similarity Postulates. Similar triangles 1. Similar Triangle Example Problems. Similar triangles 2. Similarity Example Problems. Solving similar triangles 1. Similarity example where same side plays different roles. Challenging Similarity Problem. Finding Area Using Similarity and Congruence. Similar triangles. Similar triangles (part 2).

You probably like triangles. You think they are useful. They show up a lot. What you'll see in this topic is that they are far more magical and mystical than you ever imagined!. Circumcenter of a Triangle. Circumcenter of a Right Triangle. Three Points Defining a Circle. Area Circumradius Formula Proof. 2003 AIME II Problem 7. Point Line Distance and Angle Bisectors. Incenter and incircles of a triangle. Inradius Perimeter and Area. Angle Bisector Theorem Proof. Angle Bisector Theorem Examples. Angle bisector theorem. Triangle Medians and Centroids. Triangle Medians and Centroids (2D Proof). Medians divide into smaller triangles of equal area. Exploring Medial Triangles. Proving that the Centroid is 2-3rds along the Median. Median Centroid Right Triangle Example. Proof - Triangle Altitudes are Concurrent (Orthocenter). Common Orthocenter and Centroid. Review of Triangle Properties. Euler Line. Euler's Line Proof. Constructing a perpendicular bisector using a compass and straightedge. Constructing a perpendicular line using a compass and straightedge. Constructing an angle bisector using a compass and straightedge. Compass Constructions. Circumcenter of a Triangle. Circumcenter of a Right Triangle. Three Points Defining a Circle. Area Circumradius Formula Proof. 2003 AIME II Problem 7. Point Line Distance and Angle Bisectors. Incenter and incircles of a triangle. Inradius Perimeter and Area. Angle Bisector Theorem Proof. Angle Bisector Theorem Examples. Angle bisector theorem. Triangle Medians and Centroids. Triangle Medians and Centroids (2D Proof). Medians divide into smaller triangles of equal area. Exploring Medial Triangles. Proving that the Centroid is 2-3rds along the Median. Median Centroid Right Triangle Example. Proof - Triangle Altitudes are Concurrent (Orthocenter). Common Orthocenter and Centroid. Review of Triangle Properties. Euler Line. Euler's Line Proof. Constructing a perpendicular bisector using a compass and straightedge. Constructing a perpendicular line using a compass and straightedge. Constructing an angle bisector using a compass and straightedge. Compass Constructions.

Let's think more visually about things like shifts, rotations, scaling and symmetry. Axis of symmetry. Translations of polygons. Determining a translation for a shape. Rotation of polygons example. Axis of symmetry. Translations of polygons. Determining a translation for a shape. Rotation of polygons example.

Sal does the 80 problems from the released questions from the California Standards Test for Geometry. Basic understanding of Algebra I necessary. Interesting Perimeter and Area Problems. Challenging Perimeter Problem. CA Geometry: deductive reasoning. CA Geometry: Proof by Contradiction. CA Geometry: More Proofs. CA Geometry: Similar Triangles 1. CA Geometry: Similar Triangles 2. CA Geometry: More on congruent and similar triangles. CA Geometry: Triangles and Parallelograms. CA Geometry: Area, Pythagorean Theorem. CA Geometry: Area, Circumference, Volume. CA Geometry: Pythagorean Theorem, Area. CA Geometry: Exterior Angles. CA Geometry: Deducing Angle Measures. CA Geometry: Pythagorean Theorem, Compass Constructions. CA Geometry: Compass Construction. CA Geometry: Basic Trigonometry. CA Geometry: More Trig. CA Geometry: Circle Area Chords Tangent. CA Geometry: Secants and Translations. Interesting Perimeter and Area Problems. Challenging Perimeter Problem. CA Geometry: deductive reasoning. CA Geometry: Proof by Contradiction. CA Geometry: More Proofs. CA Geometry: Similar Triangles 1. CA Geometry: Similar Triangles 2. CA Geometry: More on congruent and similar triangles. CA Geometry: Triangles and Parallelograms. CA Geometry: Area, Pythagorean Theorem. CA Geometry: Area, Circumference, Volume. CA Geometry: Pythagorean Theorem, Area. CA Geometry: Exterior Angles. CA Geometry: Deducing Angle Measures. CA Geometry: Pythagorean Theorem, Compass Constructions. CA Geometry: Compass Construction. CA Geometry: Basic Trigonometry. CA Geometry: More Trig. CA Geometry: Circle Area Chords Tangent. CA Geometry: Secants and Translations.

GMAT Math: 1. GMAT Math: 2. GMAT Math: 3. GMAT Math: 4. GMAT Math: 5. GMAT: Math 6. GMAT: Math 7. GMAT: Math 8. GMAT: Math 9. GMAT: Math 10. GMAT: Math 11. GMAT: Math 12. GMAT: Math 13. GMAT: Math 14. GMAT: Math 15. GMAT: Math 16. GMAT: Math 17. GMAT: Math 18. GMAT: Math 19. GMAT Math 20. GMAT Math 21. GMAT Math 22. GMAT Math 23. GMAT Math 24. GMAT Math 25. GMAT Math 26. GMAT Math 27. GMAT Math 28. GMAT Math 29. GMAT Math 30. GMAT Math 31. GMAT Math 32. GMAT Math 33. GMAT Math 34. GMAT Math 35. GMAT Math 36. GMAT Math 37. GMAT Math 38. GMAT Math 39. GMAT Math 40. GMAT Math 41. GMAT Math 42. GMAT Math 43. GMAT Math 44. GMAT Math 45. GMAT Math 46. GMAT Math 47. GMAT Math 48. GMAT Math 49. GMAT Math 50. GMAT Math 51. GMAT Math 52. GMAT Math 53. GMAT Math 54.

Questions from previous IIT JEEs. IIT JEE Trigonometry Problem 1. IIT JEE Perpendicular Planes (Part 1). IIT JEE Perpendicular Plane (part 2). IIT JEE Complex Root Probability (part 1). IIT JEE Complex Root Probability (part 2). IIT JEE Position Vectors. IIT JEE Integral Limit. IIT JEE Algebraic Manipulation. IIT JEE Function Maxima. IIT JEE Diameter Slope. IIT JEE Hairy Trig and Algebra (part 1). IIT JEE Hairy Trig and Algebra (Part 2). IIT JEE Hairy Trig and Algebra (Part 3). IIT JEE Complex Numbers (part 1). IIT JEE Complex Numbers (part 2). IIT JEE Complex Numbers (part 3). IIT JEE Differentiability and Boundedness. IIT JEE Integral with Binomial Expansion. IIT JEE Symmetric and Skew-Symmetric Matrices. IIT JEE Trace and Determinant. IIT JEE Divisible Determinants. IIT JEE Circle Hyperbola Intersection. IIT JEE Circle Hyperbola Common Tangent Part 1. IIT JEE Circle Hyperbola Common Tangent Part 2. IIT JEE Circle Hyperbola Common Tangent Part 3. IIT JEE Circle Hyperbola Common Tangent Part 4. IIT JEE Circle Hyperbola Common Tangent Part 5. IIT JEE Trigonometric Constraints. IIT JEE Trigonometric Maximum. Vector Triple Product Expansion (very optional). IIT JEE Lagrange's Formula. Tangent Line Hyperbola Relationship (very optional). 2010 IIT JEE Paper 1 Problem 50 Hyperbola Eccentricity. Normal vector from plane equation. Point distance to plane. Distance Between Planes. Complex Determinant Example. Series Sum Example. Trigonometric System Example. Simple Differential Equation Example. IIT JEE Trigonometry Problem 1. IIT JEE Perpendicular Planes (Part 1). IIT JEE Perpendicular Plane (part 2). IIT JEE Complex Root Probability (part 1). IIT JEE Complex Root Probability (part 2). IIT JEE Position Vectors. IIT JEE Integral Limit. IIT JEE Algebraic Manipulation. IIT JEE Function Maxima. IIT JEE Diameter Slope. IIT JEE Hairy Trig and Algebra (part 1). IIT JEE Hairy Trig and Algebra (Part 2). IIT JEE Hairy Trig and Algebra (Part 3). IIT JEE Complex Numbers (part 1). IIT JEE Complex Numbers (part 2). IIT JEE Complex Numbers (part 3). IIT JEE Differentiability and Boundedness. IIT JEE Integral with Binomial Expansion. IIT JEE Symmetric and Skew-Symmetric Matrices. IIT JEE Trace and Determinant. IIT JEE Divisible Determinants. IIT JEE Circle Hyperbola Intersection. IIT JEE Circle Hyperbola Common Tangent Part 1. IIT JEE Circle Hyperbola Common Tangent Part 2. IIT JEE Circle Hyperbola Common Tangent Part 3. IIT JEE Circle Hyperbola Common Tangent Part 4. IIT JEE Circle Hyperbola Common Tangent Part 5. IIT JEE Trigonometric Constraints. IIT JEE Trigonometric Maximum. Vector Triple Product Expansion (very optional). IIT JEE Lagrange's Formula. Tangent Line Hyperbola Relationship (very optional). 2010 IIT JEE Paper 1 Problem 50 Hyperbola Eccentricity. Normal vector from plane equation. Point distance to plane. Distance Between Planes. Complex Determinant Example. Series Sum Example. Trigonometric System Example. Simple Differential Equation Example.

This course provides a brief review of introductory algebra topics. Topics to be covered include integer operations, order of operations, perimeter and area, fractions and decimals, scientific notation, ratios and rates, conversions, percents, algebraic expressions, linear equations, the Pythagorean theorem, and graphing.

Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.

This course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines such as physics, economics and social sciences, natural sciences, and engineering. It parallels the combination of theory and applications in Professor Strang’s textbook Introduction to Linear Algebra.

Course Format

This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:

• A complete set of Lecture Videos by Professor Gilbert Strang.
• Summary Notes for all videos along with suggested readings in Prof. Strang's textbook Linear Algebra.
• Problem Solving Videos on every topic taught by an experienced MIT Recitation Instructor.
• Problem Sets to do on your own with Solutions to check your answers against when you're done.
• A selection of Java® Demonstrations to illustrate key concepts.
• A full set of Exams with Solutions, including review material to help you prepare.

Matrices, vectors, vector spaces, transformations. Covers all topics in a first year college linear algebra course. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra. Introduction to matrices. Matrix multiplication (part 1). Matrix multiplication (part 2). Idea Behind Inverting a 2x2 Matrix. Inverting matrices (part 2). Inverting Matrices (part 3). Matrices to solve a system of equations. Matrices to solve a vector combination problem. Singular Matrices. 3-variable linear equations (part 1). Solving 3 Equations with 3 Unknowns. Introduction to Vectors. Vector Examples. Parametric Representations of Lines. Linear Combinations and Span. Introduction to Linear Independence. More on linear independence. Span and Linear Independence Example. Linear Subspaces. Basis of a Subspace. Vector Dot Product and Vector Length. Proving Vector Dot Product Properties. Proof of the Cauchy-Schwarz Inequality. Vector Triangle Inequality. Defining the angle between vectors. Defining a plane in R3 with a point and normal vector. Cross Product Introduction. Proof: Relationship between cross product and sin of angle. Dot and Cross Product Comparison/Intuition. Matrices: Reduced Row Echelon Form 1. Matrices: Reduced Row Echelon Form 2. Matrices: Reduced Row Echelon Form 3. Matrix Vector Products. Introduction to the Null Space of a Matrix. Null Space 2: Calculating the null space of a matrix. Null Space 3: Relation to Linear Independence. Column Space of a Matrix. Null Space and Column Space Basis. Visualizing a Column Space as a Plane in R3. Proof: Any subspace basis has same number of elements. Dimension of the Null Space or Nullity. Dimension of the Column Space or Rank. Showing relation between basis cols and pivot cols. Showing that the candidate basis does span C(A). A more formal understanding of functions. Vector Transformations. Linear Transformations. Matrix Vector Products as Linear Transformations. Linear Transformations as Matrix Vector Products. Image of a subset under a transformation. im(T): Image of a Transformation. Preimage of a set. Preimage and Kernel Example. Sums and Scalar Multiples of Linear Transformations. More on Matrix Addition and Scalar Multiplication. Linear Transformation Examples: Scaling and Reflections. Linear Transformation Examples: Rotations in R2. Rotation in R3 around the X-axis. Unit Vectors. Introduction to Projections. Expressing a Projection on to a line as a Matrix Vector prod. Compositions of Linear Transformations 1. Compositions of Linear Transformations 2. Matrix Product Examples. Matrix Product Associativity. Distributive Property of Matrix Products. Introduction to the inverse of a function. Proof: Invertibility implies a unique solution to f(x)=y. Surjective (onto) and Injective (one-to-one) functions. Relating invertibility to being onto and one-to-one. Determining whether a transformation is onto. Exploring the solution set of Ax=b. Matrix condition for one-to-one trans. Simplifying conditions for invertibility. Showing that Inverses are Linear. Deriving a method for determining inverses. Example of Finding Matrix Inverse. Formula for 2x2 inverse. 3x3 Determinant. nxn Determinant. Determinants along other rows/cols. Rule of Sarrus of Determinants. Determinant when row multiplied by scalar. (correction) scalar multiplication of row. Determinant when row is added. Duplicate Row Determinant. Determinant after row operations. Upper Triangular Determinant. Simpler 4x4 determinant. Determinant and area of a parallelogram. Determinant as Scaling Factor. Transpose of a Matrix. Determinant of Transpose. Transpose of a Matrix Product. Transposes of sums and inverses. Transpose of a Vector. Rowspace and Left Nullspace. Visualizations of Left Nullspace and Rowspace. Orthogonal Complements. Rank(A) = Rank(transpose of A). dim(V) + dim(orthogonal complement of V)=n. Representing vectors in Rn using subspace members. Orthogonal Complement of the Orthogonal Complement. Orthogonal Complement of the Nullspace. Unique rowspace solution to Ax=b. Rowspace Solution to Ax=b example. Showing that A-transpose x A is invertible. Projections onto Subspaces. Visualizing a projection onto a plane. A Projection onto a Subspace is a Linear Transforma. Subspace Projection Matrix Example. Another Example of a Projection Matrix. Projection is closest vector in subspace. Least Squares Approximation. Least Squares Examples. Another Least Squares Example. Coordinates with Respect to a Basis. Change of Basis Matrix. Invertible Change of Basis Matrix. Transformation Matrix with Respect to a Basis. Alternate Basis Transformation Matrix Example. Alternate Basis Transformation Matrix Example Part 2. Changing coordinate systems to help find a transformation matrix. Introduction to Orthonormal Bases. Coordinates with respect to orthonormal bases. Projections onto subspaces with orthonormal bases. Finding projection onto subspace with orthonormal basis example. Example using orthogonal change-of-basis matrix to find transformation matrix. Orthogonal matrices preserve angles and lengths. The Gram-Schmidt Process. Gram-Schmidt Process Example. Gram-Schmidt example with 3 basis vectors. Introduction to Eigenvalues and Eigenvectors. Proof of formula for determining Eigenvalues. Example solving for the eigenvalues of a 2x2 matrix. Finding Eigenvectors and Eigenspaces example. Eigenvalues of a 3x3 matrix. Eigenvectors and Eigenspaces for a 3x3 matrix. Showing that an eigenbasis makes for good coordinate systems. Vector Triple Product Expansion (very optional). Normal vector from plane equation. Point distance to plane. Distance Between Planes.

We explore creating and moving between various coordinate systems. Orthogonal Complements. dim(V) + dim(orthogonal complement of V)=n. Representing vectors in Rn using subspace members. Orthogonal Complement of the Orthogonal Complement. Orthogonal Complement of the Nullspace. Unique rowspace solution to Ax=b. Rowspace Solution to Ax=b example. Projections onto Subspaces. Visualizing a projection onto a plane. A Projection onto a Subspace is a Linear Transforma. Subspace Projection Matrix Example. Another Example of a Projection Matrix. Projection is closest vector in subspace. Least Squares Approximation. Least Squares Examples. Another Least Squares Example. Coordinates with Respect to a Basis. Change of Basis Matrix. Invertible Change of Basis Matrix. Transformation Matrix with Respect to a Basis. Alternate Basis Transformation Matrix Example. Alternate Basis Transformation Matrix Example Part 2. Changing coordinate systems to help find a transformation matrix. Introduction to Orthonormal Bases. Coordinates with respect to orthonormal bases. Projections onto subspaces with orthonormal bases. Finding projection onto subspace with orthonormal basis example. Example using orthogonal change-of-basis matrix to find transformation matrix. Orthogonal matrices preserve angles and lengths. The Gram-Schmidt Process. Gram-Schmidt Process Example. Gram-Schmidt example with 3 basis vectors. Introduction to Eigenvalues and Eigenvectors. Proof of formula for determining Eigenvalues. Example solving for the eigenvalues of a 2x2 matrix. Finding Eigenvectors and Eigenspaces example. Eigenvalues of a 3x3 matrix. Eigenvectors and Eigenspaces for a 3x3 matrix. Showing that an eigenbasis makes for good coordinate systems. Orthogonal Complements. dim(V) + dim(orthogonal complement of V)=n. Representing vectors in Rn using subspace members. Orthogonal Complement of the Orthogonal Complement. Orthogonal Complement of the Nullspace. Unique rowspace solution to Ax=b. Rowspace Solution to Ax=b example. Projections onto Subspaces. Visualizing a projection onto a plane. A Projection onto a Subspace is a Linear Transforma. Subspace Projection Matrix Example. Another Example of a Projection Matrix. Projection is closest vector in subspace. Least Squares Approximation. Least Squares Examples. Another Least Squares Example. Coordinates with Respect to a Basis. Change of Basis Matrix. Invertible Change of Basis Matrix. Transformation Matrix with Respect to a Basis. Alternate Basis Transformation Matrix Example. Alternate Basis Transformation Matrix Example Part 2. Changing coordinate systems to help find a transformation matrix. Introduction to Orthonormal Bases. Coordinates with respect to orthonormal bases. Projections onto subspaces with orthonormal bases. Finding projection onto subspace with orthonormal basis example. Example using orthogonal change-of-basis matrix to find transformation matrix. Orthogonal matrices preserve angles and lengths. The Gram-Schmidt Process. Gram-Schmidt Process Example. Gram-Schmidt example with 3 basis vectors. Introduction to Eigenvalues and Eigenvectors. Proof of formula for determining Eigenvalues. Example solving for the eigenvalues of a 2x2 matrix. Finding Eigenvectors and Eigenspaces example. Eigenvalues of a 3x3 matrix. Eigenvectors and Eigenspaces for a 3x3 matrix. Showing that an eigenbasis makes for good coordinate systems.

Understanding how we can map one set of vectors to another set. Matrices used to define linear transformations. A more formal understanding of functions. Vector Transformations. Linear Transformations. Matrix Vector Products as Linear Transformations. Linear Transformations as Matrix Vector Products. Image of a subset under a transformation. im(T): Image of a Transformation. Preimage of a set. Preimage and Kernel Example. Sums and Scalar Multiples of Linear Transformations. More on Matrix Addition and Scalar Multiplication. Linear Transformation Examples: Scaling and Reflections. Linear Transformation Examples: Rotations in R2. Rotation in R3 around the X-axis. Unit Vectors. Introduction to Projections. Expressing a Projection on to a line as a Matrix Vector prod. Compositions of Linear Transformations 1. Compositions of Linear Transformations 2. Matrix Product Examples. Matrix Product Associativity. Distributive Property of Matrix Products. Introduction to the inverse of a function. Proof: Invertibility implies a unique solution to f(x)=y. Surjective (onto) and Injective (one-to-one) functions. Relating invertibility to being onto and one-to-one. Determining whether a transformation is onto. Exploring the solution set of Ax=b. Matrix condition for one-to-one trans. Simplifying conditions for invertibility. Showing that Inverses are Linear. Deriving a method for determining inverses. Example of Finding Matrix Inverse. Formula for 2x2 inverse. 3x3 Determinant. nxn Determinant. Determinants along other rows/cols. Rule of Sarrus of Determinants. Determinant when row multiplied by scalar. (correction) scalar multiplication of row. Determinant when row is added. Duplicate Row Determinant. Determinant after row operations. Upper Triangular Determinant. Simpler 4x4 determinant. Determinant and area of a parallelogram. Determinant as Scaling Factor. Transpose of a Matrix. Determinant of Transpose. Transpose of a Matrix Product. Transposes of sums and inverses. Transpose of a Vector. Rowspace and Left Nullspace. Visualizations of Left Nullspace and Rowspace. Rank(A) = Rank(transpose of A). Showing that A-transpose x A is invertible. A more formal understanding of functions. Vector Transformations. Linear Transformations. Matrix Vector Products as Linear Transformations. Linear Transformations as Matrix Vector Products. Image of a subset under a transformation. im(T): Image of a Transformation. Preimage of a set. Preimage and Kernel Example. Sums and Scalar Multiples of Linear Transformations. More on Matrix Addition and Scalar Multiplication. Linear Transformation Examples: Scaling and Reflections. Linear Transformation Examples: Rotations in R2. Rotation in R3 around the X-axis. Unit Vectors. Introduction to Projections. Expressing a Projection on to a line as a Matrix Vector prod. Compositions of Linear Transformations 1. Compositions of Linear Transformations 2. Matrix Product Examples. Matrix Product Associativity. Distributive Property of Matrix Products. Introduction to the inverse of a function. Proof: Invertibility implies a unique solution to f(x)=y. Surjective (onto) and Injective (one-to-one) functions. Relating invertibility to being onto and one-to-one. Determining whether a transformation is onto. Exploring the solution set of Ax=b. Matrix condition for one-to-one trans. Simplifying conditions for invertibility. Showing that Inverses are Linear. Deriving a method for determining inverses. Example of Finding Matrix Inverse. Formula for 2x2 inverse. 3x3 Determinant. nxn Determinant. Determinants along other rows/cols. Rule of Sarrus of Determinants. Determinant when row multiplied by scalar. (correction) scalar multiplication of row. Determinant when row is added. Duplicate Row Determinant. Determinant after row operations. Upper Triangular Determinant. Simpler 4x4 determinant. Determinant and area of a parallelogram. Determinant as Scaling Factor. Transpose of a Matrix. Determinant of Transpose. Transpose of a Matrix Product. Transposes of sums and inverses. Transpose of a Vector. Rowspace and Left Nullspace. Visualizations of Left Nullspace and Rowspace. Rank(A) = Rank(transpose of A). Showing that A-transpose x A is invertible.

Let's get our feet wet by thinking in terms of vectors and spaces. Introduction to Vectors. Vector Examples. Scaling vectors. Adding vectors. Parametric Representations of Lines. Linear Combinations and Span. Introduction to Linear Independence. More on linear independence. Span and Linear Independence Example. Linear Subspaces. Basis of a Subspace. Vector Dot Product and Vector Length. Proving Vector Dot Product Properties. Proof of the Cauchy-Schwarz Inequality. Vector Triangle Inequality. Defining the angle between vectors. Defining a plane in R3 with a point and normal vector. Cross Product Introduction. Proof: Relationship between cross product and sin of angle. Dot and Cross Product Comparison/Intuition. Vector Triple Product Expansion (very optional). Normal vector from plane equation. Point distance to plane. Distance Between Planes. Matrices: Reduced Row Echelon Form 1. Matrices: Reduced Row Echelon Form 2. Matrices: Reduced Row Echelon Form 3. Matrix Vector Products. Introduction to the Null Space of a Matrix. Null Space 2: Calculating the null space of a matrix. Null Space 3: Relation to Linear Independence. Column Space of a Matrix. Null Space and Column Space Basis. Visualizing a Column Space as a Plane in R3. Proof: Any subspace basis has same number of elements. Dimension of the Null Space or Nullity. Dimension of the Column Space or Rank. Showing relation between basis cols and pivot cols. Showing that the candidate basis does span C(A). Introduction to Vectors. Vector Examples. Scaling vectors. Adding vectors. Parametric Representations of Lines. Linear Combinations and Span. Introduction to Linear Independence. More on linear independence. Span and Linear Independence Example. Linear Subspaces. Basis of a Subspace. Vector Dot Product and Vector Length. Proving Vector Dot Product Properties. Proof of the Cauchy-Schwarz Inequality. Vector Triangle Inequality. Defining the angle between vectors. Defining a plane in R3 with a point and normal vector. Cross Product Introduction. Proof: Relationship between cross product and sin of angle. Dot and Cross Product Comparison/Intuition. Vector Triple Product Expansion (very optional). Normal vector from plane equation. Point distance to plane. Distance Between Planes. Matrices: Reduced Row Echelon Form 1. Matrices: Reduced Row Echelon Form 2. Matrices: Reduced Row Echelon Form 3. Matrix Vector Products. Introduction to the Null Space of a Matrix. Null Space 2: Calculating the null space of a matrix. Null Space 3: Relation to Linear Independence. Column Space of a Matrix. Null Space and Column Space Basis. Visualizing a Column Space as a Plane in R3. Proof: Any subspace basis has same number of elements. Dimension of the Null Space or Nullity. Dimension of the Column Space or Rank. Showing relation between basis cols and pivot cols. Showing that the candidate basis does span C(A).