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The purpose of this Warm-up is to connect the analytical work that students have done with dot plots in previous lessons with statistical questions. This activity reminds students that we gather, display, and analyze data in order to answer statistical questions. This work will be helpful as students contrast dot plots and histograms in subsequent activities.
Arrange students in groups of 2. Give students 1 minute of quiet work time, followed by 2 minutes to share their responses with a partner. Ask students to decide, during a partner discussion, if each question proposed by their partner is a statistical question that can be answered using the dot plot. Follow with a whole-class discussion.
If students have trouble getting started, consider giving a sample question that can be answered using the data on the dot plot (for example, “How many dogs weigh more than 100 pounds?”)
Here is a dot plot showing the weights, in pounds, of 40 dogs at a dog show.
Ask students to share questions that they agreed were statistical questions that could be answered using the dot plot. If there is time, consider asking students how they would find the answer to some of the statistical questions.
Display the dot plot for all to see. Ask students to share a typical weight for a dog at this dog show and why they think it is typical. Mark their answers on the displayed dot plot. After each student shares, ask the class if they agree or disagree.
This activity introduces students to histograms. By now, students have developed a good sense of dot plots as a tool for representing distributions. They use this understanding to make sense of a different form of data representation. The data set shown on the first histogram is the same one from the preceding Warm-up, so students are familiar with its distribution. This allows them to focus on making sense of the features of the new representation and comparing them to the corresponding dot plot.
At this point students do not yet need to see the merits or limits of histograms and dot plots. Students should recognize, however, how the structures of the two displays are different (MP7) and start to see that the structural differences affect the insights we are able to glean from the displays.
Explain to students that they will now explore histograms, another way to represent numerical data. Give students 3–4 minutes of quiet work time, and then 2–3 minutes to share their responses with a partner. Follow with a whole-class discussion.
Use Collect and Display to create a shared reference that captures students’ developing mathematical language. Collect the language that students use to discuss how dot plots and histograms are alike and different. Display words and phrases such as “precise,” “frequency,” “distribution,” “center,” and “spread.”
Here is a histogram that shows some dog weights in pounds.
Each bar includes the left-end value but not the right-end value. For example, the first bar includes dogs that weigh 60 pounds and 68 pounds but not 80 pounds. An 80-pound dog would be included in the second bar with a frequency of 11.
Use the histogram to answer these questions.
How many dogs weigh between 100 and a little less than 120 pounds?
How many dogs weigh exactly 70 pounds?
How many dogs weigh at least 120 pounds?
How much does the heaviest dog at the show weigh?
Discuss with a partner:
If you used the dot plot to answer the same five questions you just answered, how would your answers be different?
How are the histogram and the dot plot alike? How are they different?
Ask a few students to briefly share their responses to the first set of questions to make sure that students are able to read and interpret the graph correctly.
Then direct students' attention to the reference created using Collect and Display. Ask students to share their comparison of dot plots and histograms. Invite students to borrow language from the display as needed, and update the reference to include additional phrases as they respond. (For example, “The histogram is less precise, but you can still see the distribution. The center and spread appear similar in both.”)
If not already mentioned by students, highlight that, in a histogram:
In this activity, students use histograms to compare two groups by studying the shape, center, and spread of each distribution. Although histograms are not precise, often they can be enough to make a general comparison of groups.
Arrange students in groups of 2. Give students 4–5 minutes of quiet work time and 1–2 minutes to share their responses with a partner.
Professional basketball players tend to be taller than professional baseball players.
Here are two histograms that show height distributions of 50 professional baseball players and 50 professional basketball players.
Use Stronger and Clearer Each Time to give students an opportunity to revise and refine their response to the questions about describing the distribution of heights of basketball and baseball players. In this structured pairing strategy, students bring their first draft response into conversations with 2–3 different partners. They take turns being the speaker and the listener. As the speaker, students share their initial ideas and read their first draft. As the listener, students ask questions and give feedback that will help clarify and strengthen their partner’s ideas and writing.
If time allows, display these prompts for feedback:
“$\underline{\hspace{.5in}}$ makes sense, but what do you mean when you say $\underline{\hspace{.5in}}$?”
“Can you describe that another way?”
“How do you know $\underline{\hspace{.5in}}$ ? What else do you know is true?”
Close the partner conversations, and give students 3–5 minutes to revise their first draft. Encourage students to incorporate any good ideas and words they got from their partners to make their next draft stronger and clearer. If time allows, invite students to compare their first and final drafts. Select 2–3 students to share how their drafts changed and why they made the changes they did.
After Stronger and Clearer Each Time, highlight the fact that students are using approximations of center and different adjectives to characterize a distribution or a typical height and that, as a result, there are variations in our descriptions. In some situations, these variations might make it challenging to compare groups more precisely.
If time allows, remind students that this type of analysis uses trends to compare groups, not individuals. There are some baseball players that are taller than some basketball players in these groups, so we cannot determine which sport each person plays based on their height.
A histogram is a visual representation of data that groups values together in intervals, or “bins,” to combine their frequency. This histogram, for instance, represents the distribution for the weights of some dogs.
In addition to using dot plots, we can also represent distributions of numerical data using histograms.
Here is a dot plot that shows the weights, in kilograms, of 30 dogs, followed by a histogram that shows the same distribution.
In a histogram, data values are placed in groups, or “bins,” of a certain size, and each group is represented with a bar. The height of the bar tells us the frequency for that group.
For example, the height of the tallest bar is 10, and the bar represents weights from 20 to less than 25 kilograms, so there are 10 dogs whose weights fall in that group. Similarly, there are 3 dogs that weigh anywhere from 25 to less than 30 kilograms.
Notice that the histogram and the dot plot have a similar shape. The dot plot has the advantage of showing all of the data values, but the histogram is easier to draw and to interpret when there are a lot of values or when the values are all different.
The histogram allows us to learn more about the dog weight distribution and describe its center and spread.