The Size of the Scale Factor: IM 7.1.5
[url=https://im.kendallhunt.com/MS/teachers/2/1/5/preparation.html]“Scaled Relationships”[/url] from IM Grade 7 by [url=https://www.geogebra.org/m/gus8ffvr]Open Up Resources[/url] and Illustrative Mathematics. Licensed under the [url=https://creativecommons.org/licenses/by/4.0/]Creative Commons Attribution 4.0 license[/url].
Table of Contents
- Lesson 7.1.5
- IM 7.1.5 Lesson: The Size of the Scale Factor
- Practice 7.1.5
- IM 7.1.5 Practice: The Size of the Scale Factor
IM 7.1.5 Lesson: The Size of the Scale Factor
Solve the equation mentally.
[math]16x=176[/math]
[math]16x=8[/math]
[math]16x=1[/math]
[math]\frac{1}{5}x=1[/math]
[math]\frac{2}{5}x=1[/math]
Here is a set of cards. On each card, Figure A is the original and Figure B is a scaled copy.
Sort the cards based on their scale factors. Be prepared to explain your reasoning.[br]
Examine cards 10 and 13 more closely. What do you notice about the shapes and sizes of the figures? What do you notice about the scale factors?[br]
Examine cards 8 and 12 more closely. What do you notice about the figures? What do you notice about the scale factors?[br]
[size=150]Triangle B is a scaled copy of Triangle A with scale factor [math]\frac{1}{2}[/math]. [/size][br]How many times bigger are the side lengths of Triangle B when compared with Triangle A?[br]
Imagine you scale Triangle B by a scale factor of [math]\frac{1}{2}[/math] to get Triangle C. How many times bigger will the side lengths of Triangle C be when compared with Triangle A?[br]
Triangle B has been scaled once. Triangle C has been scaled twice. Imagine you scale triangle A [math]n[/math] times to get Triangle N, always using a scale factor of [math]\frac{1}{2}[/math]. How many times bigger will the side lengths of Triangle N be when compared with Triangle A?
Your teacher will give you 2 pieces of a 6-piece puzzle.[br][br]If you drew scaled copies of your puzzle pieces using a scale factor of [math]\frac{1}{2}[/math], would they be larger or smaller than the original pieces? How do you know?[br]
Create a scaled copy of your 2 puzzle pieces on a blank square, with a scale factor of [math]\frac{1}{2}[/math].
When everyone in your group is finished, put all 6 of the original puzzle pieces together like this:[br][br][img]data:image/png;base64,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[/img][br][br]Next, put all 6 of your scaled copies together. Compare your scaled puzzle with the original puzzle. Which parts seem to be scaled correctly and which seem off? What might have caused those parts to be off?[br][br]*Revise any of the scaled copies that may have been drawn incorrectly.
If you were to lose one of the pieces of the original puzzle, but still had the scaled copy, how could you recreate the lost piece? [i]Explain[/i].
What is the scale factor from the original triangle in the applet below to its copy? Explain or show your reasoning.
The scale factor from the original trapezoid to its copy is 2. Draw the scaled copy.
The scale factor from the original figure to its copy is ³⁄₂. Draw the original figure.
What is the scale factor from the original figure to the copy in the applet below? Explain how you know.
The scale factor from the original figure to its scaled copy is 3. Draw the scaled copy.
IM 7.1.5 Practice: The Size of the Scale Factor
Rectangles P, Q, R, and S are scaled copies of one another. Select [b]all [/b]the pairs with a scale factor [i]greater than 1[/i].[br][img]data:image/png;base64,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[/img]
Rectangles P, Q, R, and S are scaled copies of one another. Select [b]all [/b]the pairs with a scale factor [i]equal to 1.[br][/i][br][img]data:image/png;base64,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[/img]
Rectangles P, Q, R, and S are scaled copies of one another. Select [b]all [/b]the pairs with a scale factor[i] less than 1.[/i][br][br][img]data:image/png;base64,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[/img]
Triangle S and Triangle L are scaled copies of one another.
[img]data:image/png;base64,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[/img][br][br][br]What is the scale factor from S to L?
What is the scale factor from L to S?
Triangle M is also a scaled copy of S. The scale factor from S to M is [math]\frac{3}{2}[/math]. What is the scale factor from M to S?
Are two squares with the same side lengths scaled copies of one another? Explain your reasoning.
Quadrilateral A has side lengths 2, 3, 5, and 6. Quadrilateral B has side lengths 4, 5, 8, and 10. Could one of the quadrilaterals be a scaled copy of the other? Explain.
Select [b]all [/b]the ratios that are equivalent to the ratio [math]12:3[/math].