Linear programming is when you have an objective function under a system of constraints. We graphed the constraints, then found the vertices that bound the system. Each vertex can then be plugged into the objective function and simplified to find the maximum of minimum value of the objective function. Hunter worked on problems p. 142 (1-9)
We then moved onto Chapter 4. Section 4-1 is an introduction to matrices, where Hunter learned that matrices are identified by their size (row x column). Elements of a matrix are identified by a subscript (row, column). Hunter did exercises p. 170 (1-11, 20-25) p. 173 (30, 31)