Fossils and Flags

40 min

Narrative

The mathematical purpose of this activity is for students to collect, summarize, interpret, and draw conclusions from bivariate data using scatter plots, best-fit lines, residuals and correlation coefficients. Students measure the approximate lengths of the humerus bone and heights of their classmates to collect data and create a linear model. The model is then used to approximate the height of an ancient human based on the length of a found humerus bone.

Making graphing technology available gives students an opportunity to choose appropriate tools strategically (MP5). By collecting their own data and using a best-fit line to find additional information, students are modeling with mathematics (MP4).

Launch

Arrange students in groups of 2 to 4. Present the task to students, and ask them to brainstorm different ways that they could answer the question. After 2 minutes of quiet think time, ask students to share their ideas with the class. The remaining time should be used by students to collect, analyze, summarize, and interpret the data.

MLR5 Co-Craft Questions. Keep books or devices closed. Display only the first sentence of this problem (“An anthropologist finds a fossilized humerus bone of an ancient human ancestor.”), without revealing the task, and ask students to write down possible mathematical questions that could be asked about the situation. Invite students to compare their questions before revealing the task. Ask, “What do these questions have in common? How are they different?” Reveal the intended questions for this task, and invite additional connections.
Advances: Reading, Writing

Student Task

<p>Arm skeletal system</p>

An anthropologist finds a fossilized humerus bone of an ancient human ancestor. The humerus is an arm bone running from the shoulder to the elbow. It is 24 centimeters in length. Use data from your classmates to estimate the height of this ancient human.

Sample Response

Sample response: About 123 centimeters (around 4 feet). I measured the humerus and height of several classmates and created a scatter plot. I used a plot of the residuals and found that a linear model seemed to be appropriate. I then found the line of best fit to be about y=5.1x+0.2y = 5.1 x + 0.2, where yy is the height in centimeters and xx is the length of the humerus in centimeters. Using 24 centimeters for xx, I found that 5.124+0.2=122.65.1 \boldcdot 24 + 0.2 = 122.6, which I rounded since this is a rough estimate.

Synthesis

The purpose of this discussion is for students to communicate how they used mathematics to justify their findings.

Ask students:

  • “How confident are you in your answer? What information helped you determine your confidence?” (Not very confident. Since the correlation coefficient is near 0.6, there is only a moderate relationship between height and humerus length. Additionally, this ancient human ancestor may have a different anatomy—for example, apes tend to have proportionally longer arms than humans do.)
  • “How did you use mathematics to estimate the height of the ancient human?” (First, I collected data on the height and the approximate length of the humerus of my classmates. I then made a scatter plot to determine whether or not a linear model was appropriate and then computed a line of best fit. I substituted 24 centimeters into my line of best fit and obtained my answer.)
  • “Do you think that the way you measured the humerus of your classmates impacted your choice of linear model? Explain your reasoning.” (Yes, I think that I probably overestimated the bone length because I was measuring from the outside and not the inside. I think that my model likely overestimates height.)
Anticipated Misconceptions

Students may find it difficult to start to answer the question. Ask students what are the variables given in the situation. Ask students if there is a way we could collect information from people in the classroom to help answer the question.

Standards
Addressing
  • HSS-ID.B.6·Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
  • HSS-ID.C.7·Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.
  • HSS-ID.C.8·Compute (using technology) and interpret the correlation coefficient of a linear fit.
  • HSS-ID.C.9·Distinguish between correlation and causation.
  • S-ID.6·Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
  • S-ID.6·Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
  • S-ID.6·Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
  • S-ID.7·Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.
  • S-ID.7·Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.
  • S-ID.7·Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.
  • S-ID.8·Compute (using technology) and interpret the correlation coefficient of a linear fit.
  • S-ID.8·Compute (using technology) and interpret the correlation coefficient of a linear fit.
  • S-ID.8·Compute (using technology) and interpret the correlation coefficient of a linear fit.
  • S-ID.9·Distinguish between correlation and causation.
  • S-ID.9·Distinguish between correlation and causation.
  • S-ID.9·Distinguish between correlation and causation.

40 min