1. MATRICES MATRIX OPERATIONS

2. About Matrices  A matrix is a rectangular arrangement of numbers in rows and columns. Rows run horizontally and columns run vertically.  The dimensions of a matrix are stated “m x n” where ‘m’ is the number of rows and ‘n’ is the number of columns.

3. Equal Matrices Two matrices are considered equal if they have the same number of rows and columns (the same dimensions) AND all their corresponding elements are exactly the same.

4. Special Matrices Some matrices have special names because of what they look like. a)Row matrix: only has 1 row. b)Column matrix: only has 1 column. c)Square matrix: has the same number of rows and columns. d)Zero matrix: contains all zeros.

5. Matrix Addition  You can add or subtract matrices if they have the same dimensions (same number of rows and columns).  To do this, you add (or subtract) the corresponding numbers (numbers in the same positions).

6. Matrix Addition Example:

7. Real-Life Example Let’s say you’re in avid reader, and in June, July, and August you read fiction and non-fiction books, and magazines, both in paper copies and online. You want to keep track of how many different types of books and magazines you read, and store that information in matrices. Here is that information, and how it would look in matrix form:

8. Solution We can add matrices if the dimensions are the same; since the three matrices are all “3 by 2”, we can add them. For example, if we wanted to know the total number of each type of book/magazine we read, we could add each of the elements to get the sum:

9. Scalar Multiplication  To do this, multiply each entry in the matrix by the number outside (called the scalar). This is like distributing a number to a polynomial.

10. Scalar Multiplication Example:

11. Matrix Multiplication  Matrix Multiplication is NOT Commutative! Order matters!  You can multiply matrices only if the number of columns in the first matrix equals the number of rows in the second matrix. 2 columns 2 rows

12. Matrix Multiplication  Take the numbers in the first row of matrix #1. Multiply each number by its corresponding number in the first column of matrix #2. Total these products. The result, 11, goes in row 1, column 1 of the answer. Repeat with row 1, column 2; row 1 column 3; row 2, column 1;... 2(1)+3(3)=11

13. Matrix Multiplication  Notice the dimensions of the matrices and their product. 3 x 22 x 33 x 3 __

14. Matrix Multiplication  Another example: 3 x 22 x 13 x 1

15. Real-World Application Let’s say we want to find the final grades for 3 girls, and we know what their averages are for tests, projects, homework, and quizzes. We also know that tests are 40% of the grade, projects 15%, homework 25%, and quizzes 20%.

16. Solution So Alexandra has a 90, Megan has a 77, and Brittney has an 87.

17. Matrix Determinants  A Determinant is a real number associated with a matrix. Only SQUARE matrices have a determinant.  The symbol for a determinant can be the phrase “det” in front of a matrix variable, det(A); or vertical bars around a matrix, |A| or.

18. Matrix Determinants To find the determinant of a 2 x 2 matrix, multiply diagonal #1 and subtract the product of diagonal #2. Diagonal 1 = 12 Diagonal 2 = -2

19. Matrix Determinants To find the determinant of a 3 x 3 matrix, first recopy the first two columns. Then do 6 diagonal products. -20 -24 36 18 6016

20. Matrix Determinants The determinant of the matrix is the sum of the downwards products minus the sum of the upwards products. -20 -24 36 18 6016 = (-8) - (94) = -102

21. Identity Matrices  An identity matrix is a square matrix that has 1’s along the main diagonal and 0’s everywhere else.  When you multiply a matrix by the identity matrix, you get the original matrix.

22. Inverse Matrices  When you multiply a matrix and its inverse, you get the identity matrix.

23. Inverse Matrices  Not all matrices have an inverse!  To find the inverse of a 2 x 2 matrix, first find the determinant. a)If the determinant = 0, the inverse does not exist!  The inverse of a 2 x 2 matrix is the reciprocal of the determinant times the matrix with the main diagonal swapped and the other terms multiplied by -1.

24. Inverse Matrices Example 1:

25. Inverse Matrices Example 2: