Connecting Piecewise Functions to Graphs and Contexts

Explore how piecewise-defined functions are built from multiple rules. Connect each piece of the function to its corresponding graph segment and to the motion of a remote car.
Putting It All Together
[i]Answer these open ended questions on your own or with others to form deeper math connections.[/i]
What do the parts of a single line in the equation of a piecewise function represent? For example, given the following equation: [br][img]https://cdn.geogebra.org/resource/xb89epvv/KL8XNAYt9pOmT1vB/material-xb89epvv.png[/img]
What does [math]3x[/math] represent? What does [math]0\le x<4[/math] mean in relation to [math]3x[/math]?
Given the function[br][img]data:image/png;base64,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[/img][br]calculate:[br][list][*]f(1)[br][/*][*]f(-8)[br][/*][*]f(2)[br][/*][*]f(1000)[br][/*][/list]
What other real-world scenarios can be modeled using piecewise functions?
Luk

Information: Connecting Piecewise Functions to Graphs and Contexts