A linear equation is a line, and a linear inequality is a half-plane.
Every solution of sits on one line. Every solution of sits on one side of that line. The boundary is solid when the line is included ( or ) and dashed when it isn't ( or ).
Unit 3 is about lines and the regions they cut out of the coordinate plane, and how to use several of them at once to describe real limits. After this unit you should be able to solve systems of equations by graphing, substitution, and elimination, graph systems of inequalities, and use linear programming to find the best outcome under constraints.
Read the overview for the big picture, then work through each review note and answer its checkpoint question before checking the answer.
This unit builds on the linear equations you already know and asks you to handle several conditions at the same time. You'll move between equations, graphs, and word problems. The unit ends with linear programming, which ties all of those pieces together.
Honors Algebra II Unit 3 covers linear equations and inequalities in two variables, systems of linear equations and inequalities, and linear programming. You write and graph lines in slope-intercept, point-slope, and standard form, and you shade half-planes for inequalities using solid or dashed boundaries. You solve systems by graphing, substitution, and elimination, and you classify them as having one solution, no solution, or infinitely many solutions. Then you set up constraints and an objective function, graph the feasible region, and check whether a maximum or minimum exists. When the feasible region is closed and has vertices, you can test them to find an optimal value if one exists. Exact topics and order vary by school, but these skills lead directly into precalculus.
Every solution of sits on one line. Every solution of sits on one side of that line. The boundary is solid when the line is included ( or ) and dashed when it isn't ( or ).
For two equations, that's the intersection point, or no point if the lines are parallel, or every point if the lines are the same. For inequalities, it's the overlap of all the shaded regions. Substitution and elimination give exact answers when a graph can't.
Constraints create a feasible region, which may be bounded or unbounded. For a closed feasible region with vertices, an objective function such as profit reaches an optimal value at a vertex if an optimal value exists.
Lines and half-planes are the building blocks. A system's solution set contains every point that satisfies all its conditions, and it can be empty. Linear programming adds a goal and uses the feasible region to find an optimal value when one exists.
A system of linear equations is two or more equations involving the same variables.
Linear programming finds the maximum or minimum value of a linear expression when the variables must follow a set of linear inequalities.
A linear equation in two variables graphs as a straight line, and every point on the line is a solution.
Open this guide for a closer review of the topic.
A system of linear equations is two or more equations involving the same variables. For a system in two variables, the solution set contains every ordered pair that makes all the equations true at once. On a graph, those are the points shared by all the lines.
You have three ways to solve a system. Graphing shows the picture but can miss fractional answers. Substitution works best when one variable is already alone or has a coefficient of 1. Elimination works best when the equations are in standard form and you can scale them so one variable cancels.
Worked example. Solve and . The second equation gives . Substitute that into the first equation to get , so and . Then . Check in the first equation, where is true. The solution is .
When solving two line equations, a false statement like means the lines are distinct and parallel, so there is no solution. A true statement like means the equations describe the same line, so there are infinitely many solutions.
For a system of inequalities, the solution is the overlap of all the shaded half-planes. That overlap can be a region, a line, a point, or empty. A point counts only if it satisfies every inequality, and points on a dashed boundary are not included.
Check yourself: Solve and . (Answer: Add the equations to get , so . Then gives , so the solution is .)
| Case | Slopes and intercepts for nonvertical lines | What the algebra shows | Number of solutions |
|---|---|---|---|
| Lines cross | Different slopes | A single value for each variable | Exactly one |
| Parallel lines | Same slope, different y-intercepts | A false statement such as $0 = 5$ | None |
| Same line | Same slope, same y-intercept | A true statement such as $0 = 0$ | Infinitely many |
Linear programming finds the maximum or minimum value of a linear expression when the variables must follow a set of linear inequalities. Every problem has three parts. The decision variables are the quantities you choose. The constraints are the limits on those quantities. The objective function is the quantity you want to maximize or minimize.
Graph all the constraints, including and when negative amounts make no sense. The overlap of the shaded regions is the feasible region. For a closed feasible region with vertices, the Corner Point Theorem says that an optimal value, if one exists, occurs at a vertex. Testing the vertices finds an optimal value, though other points may also give that value.
Worked example. A bakery makes trays of muffins and trays of cookies. Oven space gives , and labor gives , with . Profit is . The vertices are , , , and the intersection of with . Subtracting those equations gives , so and . Testing each vertex gives , , , and . The maximum profit is 38 dollars at 6 muffin trays and 4 cookie trays.
If the region is unbounded, a maximum or minimum might not exist, so check before you report one.
Check yourself: With vertices , , , and , where does reach its maximum? (Answer: The values are 0, 16, 22, and 20, so the maximum is 22 at .)
A linear equation in two variables graphs as a straight line, and every point on the line is a solution. For two points with , the slope is the rate of change. Horizontal lines have slope 0, and vertical lines have undefined slope. In context, the slope is a rate like dollars per hour, and the y-intercept is a starting value like a flat fee.
You'll use three forms. Slope-intercept form is , point-slope form is , and standard form is . A nonvertical line can be written in any of these forms, so pick the form that matches the information you have. A vertical line can be written in standard form, but not in slope-intercept or point-slope form.
Worked example. Find the line through and . The slope is . Point-slope form gives . Distribute to get , which is in standard form.
To graph an inequality, draw the boundary line, solid for or and dashed for or . Then test a point not on the line, usually . If the test point makes the inequality true, shade its side. If you multiply or divide both sides by a negative number while solving, flip the inequality symbol.
Check yourself: For , is the boundary solid or dashed, and which side do you shade? (Answer: It's dashed because the symbol is . Testing gives , which is true, so shade the side containing the origin. That's the region above .)
| Form | Equation | Use it when |
|---|---|---|
| Slope-intercept | $y = mx + b$ | You know the slope and y-intercept or want to graph quickly |
| Point-slope | $y - y_1 = m(x - x_1)$ | You know a slope and one point, or two points |
| Standard | $Ax + By = C$ | You want intercepts fast or plan to use elimination |
| Term | Definition |
|---|---|
| System of linear equations | Two or more linear equations with the same variables, solved together by finding values that satisfy all of them. |
| Half-plane | The region on one side of a line, which is the graph of a single linear inequality. |
| Slope-intercept form | The equation $y = mx + b$, where $m$ is the slope and $b$ is the y-intercept. |
| Point-slope form | The equation $y - y_1 = m(x - x_1)$, built from one known point and the slope. |
| Standard form | The equation $Ax + By = C$, where $A$ and $B$ are not both zero. |
| Constraint | A linear inequality that limits the possible values of the variables, such as a budget or time limit. |
| Feasible region | The overlap of all constraint regions, containing every point that satisfies the whole system. |
| Vertex | A corner of the feasible region where two boundary lines intersect. |
| Objective function | The linear expression maximized or minimized in a linear programming problem. |
Multiplying by a negative reverses the order of numbers, so the symbol has to reverse too. For example, becomes after dividing by . Adding or subtracting never flips the sign. Multiplying or dividing by a negative always does.
The rule "less than means shade below" only works once the inequality is in the form . In the symbol is , but solving gives , so you shade above. A test point such as identifies the correct side when it is not on the boundary line.
When solving two line equations, both variables may cancel. A true statement like means the lines are the same and there are infinitely many solutions. A false statement like means the lines are distinct and parallel, so there are no solutions. Neither result means the answer is .
If you leave out a required constraint, such as or , or forget a vertex, you can miss the true maximum. List every boundary line, find every corner of the feasible region, and evaluate the objective function at all of them before you compare.