In order to tie comments to specific locations in the book, I have used the available page ruler sheet to identify lines in the text. A copy of that page ruler sheet can be printed from The Index Sheet.
Chapter 2: Systems of Linear Equations and Matrices | ||||||||||||||||||||||||||
2.1 Systems of Two Equations in Two Unknowns | ||||||||||||||||||||||||||
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126 | 39 | The text states that it is impossible to find the solution graphically. Of course, we could do it graphically on the
calculator and come so close that we could guess the solution.
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138 | 37 | Not that we use it all that often, but the term Inconsistent means that there is no solution for the system of equations. This is an important concept. | ||||||||||||||||||||||||
129 | 19 | The same can be said for the terms Redundant or Dependent describing situations where there are infinitely many solutions. Because we have repeated an equation, possibly in a different form but just a repeat of another equation, we really have one equation in two unkowns. Our ideal is to have two unique equations in two unkowns. When we expand our systems to three unknowns we will want three unique equations, and so on. | ||||||||||||||||||||||||
2.2 Using Matrices to Solve Systems of Equations | ||||||||||||||||||||||||||
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137 | 30 | Although the expansion to more unkowns gets messy quickly, it is important to note that whereas two variables can be represented as coordinate axes on a plane and an equation of the form Ax + By = C represents a line in that plane, three variables can be represented as space (3-dimensions) marked off by a three-way coordinate axes system (length, width, height) and an equation of the form Ax + By + Cz = =D represents a plane in that space. | ||||||||||||||||||||||||
139 | 37 | There is a subtle switch here. Before the text just talked about multiplying a row by a non-zero constant or adding two rows to get a new one. Now, in the Elementary Row Operations, the book talks about replacing a row by the product of a non-zero constant and the old contents of that row, or replacing a row by the probuct of some non-zero number times the old contents of the row plus or minus some constant times another row. | ||||||||||||||||||||||||
139 | 37 | The first note off to the side, the one marked as * NOTE, deserves a bit more attention. We will actually follow the "Some mathematicians insist that a=1 in and operation of Type 2." We will do this because that is what our calculator will insist on doing. The command for this elementary row operation is: | ||||||||||||||||||||||||
140 | 36 | I find the book explanation of the Gauss-Jordan reduction to be too hard to follow, mainly because we do not know where we are going. I will try to generate a web page with an alternate explanation and description, but it may take a bit to do that. | ||||||||||||||||||||||||
146 | 14 | The example of an Inconsistent System is important in that you need to see that the matrix ends up with an impossible row, one with all zero values except for the last item. | ||||||||||||||||||||||||
146 | 37 | The example of infinitely many solutions is important in that you need to see that you end up with a row of all zero values. That is similar to but different than the Inconsistent example given above it. | ||||||||||||||||||||||||
The web page Elementary Row Operations of the TI-83 goes through the steps to use the elementary row operations on the TI-83 to take a matrix and put it through the Gauss-Jordan method. Please note that the page assumes that you know how to create a matrix on the calculator. To help in that the page does point you to the first 36 Figures of another page. If you are not comfortable using the elementary row operations, it is worth reviewing these pages. | ||||||||||||||||||||||||||
2.3. Applications of Systems of Linear Equations | ||||||||||||||||||||||||||
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©Roger M. Palay
Saline, MI 48176
September, 2010