Lesson 5Reasoning About Square Roots
Let’s approximate square roots.
Learning Targets:
 When I have a square root, I can reason about which two whole numbers it is between.
5.1 True or False: Squared
Decide if each statement is true or false.
5.2 Square Root Values
What two whole numbers does each square root lie between? Be prepared to explain your reasoning.
Are you ready for more?
5.3 Solutions on a Number Line
The numbers , , and are positive, and , , and .
 Plot , , and on the number line. Be prepared to share your reasoning with the class.
 Plot on the number line.
Lesson 5 Summary
In general, we can approximate the values of square roots by observing the whole numbers around it, and remembering the relationship between square roots and squares. Here are some examples:
 is a little more than 8, because is a little more than and .
 is a little less than 9, because is a little less than and .
 is between 8 and 9 (it’s 8 point something), because 75 is between 64 and 81.
 is approximately 8.67, because .
If we want to find a square root between two whole numbers, we can work in the other direction. For example, since and , then we know that (to pick one possibility) is between 22 and 23.
Many calculators have a square root command, which makes it simple to find an approximate value of a square root.
Lesson 5 Practice Problems


Explain how you know that is a little more than 6.

Explain how you know that is a little less than 10.

Explain how you know that is between 5 and 6.


Plot each number on the number line:

Mark and label the positions of two square root values between 7 and 8 on the number line.

Select all the irrational numbers in the list.

Each grid square represents 1 square unit. What is the exact side length of the shaded square?

For each pair of numbers, which of the two numbers is larger? Estimate how many times larger.
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The scatter plot shows the heights (in inches) and threepoint percentages for different basketball players last season.
 Circle any data points that appear to be outliers.
 Compare any outliers to the values predicted by the model.