## Day 124 - Coaching sheets - comparing distributions.docx - Section 3: Task

*Day 124 - Coaching sheets - comparing distributions.docx*

# Comparing Distributions Part II

Lesson 4 of 11

## Objective: SWBAT compare two sets of data by describing the center or variability.

#### Do Now

*10 min*

Students enter silently according to the daily entrance routine. Today’s assignment includes some of the most commonly missed question-types from the most recent mock interim exam. When we review the answers, I make sure to focus on the third question, about overtime. This item was especially confusing on their unit test due to the wording and the students being unfamiliar with the context. I only changed the name and the numbers in the word problem to allow review of the complexity of the words in the original problem.

Students often make mistakes in problems like these because they simply do not understand the wording or what is happening in the problem. There's information they know, information they don't, and they have to figure out how to put it all together to go in search of the answer. *Forming a plan or having problem solving strategies, like the use of the bar models can help with these struggles.*

Students worked for 5 minutes to complete these three problems and must enter their answers into Senteo clickers. This allows me to generate instant data for each class. This way, I can prioritize which problems we should review given the constraints of time.

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#### Class Notes

*15 min*

Next, students are given a copy of the class notes. They are asked to fill out the heading and the aim, which is displayed on the SmartBoard. We will review measures of central tendency vs. measures of variation and discuss how each of these can help us to compare distributions.

We begin by reviewing **what** each measure describes:

- measures of central tendency summarize the data using a “typical” number
- measures of variation describe how the numbers vary, or how spread out the values are

Next, we identify different measures of center (mean, median, mode) and of variation (range, interquartile range, mean absolute deviation). Once we have identified the purpose of each measure and the different types which can be used, we are ready for an example.

I ask one student to read the work problem at the bottom of the notes. Then, I ask students to take one full minute to read each of the temperatures per city, per month. I ask the question…

- How would you describe the temperatures in New York City? San Francisco?

… and call on two to three different students to share. Then I ask them to calculate the mean and the range in temperatures per city, given calculators. This must be done independently. After 1 – 2 minutes, we make sure to have the same values and I ask:

- How do these numbers support some of the things that (students name) and (other student name) said they noticed about the temperatures earlier?

The aim in this final discussion is to get students to understand that while the averages are very close in value, the ranges indicate that the temperatures in NYC vary much more than the temperatures in San Francisco. Students should be able to explain **in their own words** what this means. What does it mean that the temperatures **vary more**? This is a great way to assess whether or not different students understand the concept of variation within statistics.

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#### Task

*20 min*

Students are given their classwork and placed in groups of 4.** I predetermine these groups before the lesson and make sure to mix the kids within each group**. There should be at least one student who has proven to understand and explain complex math topics within this group. This student will be the

**, placed in charge of ensuring everyone in their group is able to explain the complex ideas included in each question on paper and out loud. These students are pulled to the side for about 3 minutes and given Coaching sheets where they must report the progress of each student in their group.**

*table leader*

*They are asked not to give away the answer but instead wait until the student they are helping has stated and defended their own answer.*Students are allowed to work for 15 minutes to complete the class work. As I walk around during this time, I will be assigning each group a question that will need to be put up on the board during the last 5 minutes of this section. Each group must elect one student (NOT the table leader) to explain the solution to their given problem. Two other students will be responsible for putting the work on the board in the last 5 minutes of their “work time”.

In the last 5 minutes of this section the elected student from each group will explain their solutions which should already be on the chalkboard.

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#### Closing

*10 min*

After we review the solutions to each problem, students will need to return to their seats for an exit ticket.The problems covered on the exit tickets will review the same skill practiced today: *comparing distributions and variability in data sets.*

Homework will also be displayed on the SmartBoard. Students will need to turn in their exit ticket at the door, before leaving class.

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##### Similar Lessons

Environment: Suburban

- UNIT 1: Integers
- UNIT 2: Operations with Rational Numbers
- UNIT 3: Expressions and Equations - The Basics
- UNIT 4: Multi-step Equations, Inequalities, and Factoring
- UNIT 5: Ratios and Proportional Relationships
- UNIT 6: Percent Applications
- UNIT 7: Statistics and Probability
- UNIT 8: Test Prep
- UNIT 9: Geometry

- LESSON 1: Central Tendency
- LESSON 2: Comparing Distributions
- LESSON 3: Line plot & Stem-and-Leaf Plot
- LESSON 4: Comparing Distributions Part II
- LESSON 5: Variability
- LESSON 6: Measures of Variation - Range and IQR
- LESSON 7: Box and Whisker Plots
- LESSON 8: Mean Absolute Deviation
- LESSON 9: Quiz + The Language of Probability
- LESSON 10: Theoretical vs Experimental Probabilities
- LESSON 11: Compound Probability