Models and Applications

This article uses algebraic logic to solve very specific problems. Although intelligence analysis can be a bit messier than algebra, the process is essentially the same. We use our information (datasets) and the questions we need to answer (requirements) to define our real-world problem. We use analytic techniques, rather than linear equations, as our roadmaps, and we find solutions (findings) that we communicate in a standardized language, ensuring our decision-maker understands the reliability of our information, our confidence in our analysis, and the degree to which our estimates are likely to be the future outcomes. We go from A to B, but not always in a straight line.

Introduction

Learning Objectives


In this section you will:

  • Set up a linear equation to solve a real-world application.
  • Use a formula to solve a real-world application.


Josh is hoping to get an A in his college algebra class. He has scores of 75, 82, 95, 91, and 94 on his first five tests. Only the final exam remains, and the maximum of points that can be earned is 100. Is it possible for Josh to end the course with an A? A simple linear equation will give Josh his answer.

Many real-world applications can be modeled by linear equations. For example, a cell phone package may include a monthly service fee plus a charge per minute of talk-time; it costs a widget manufacturer a certain amount to produce x widgets per month plus monthly operating charges; a car rental company charges a daily fee plus an amount per mile driven. These are examples of applications we come across every day that are modeled by linear equations. In this section, we will set up and use linear equations to solve such problems.

Source: OpenStax, https://opentextbc.ca/collegealgebraopenstax/chapter/models-and-applications/
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