##### Teaching Phase: How will the teacher present the concept or skill to students?

This lesson is a project that will be completed over several days. Teacher may choose for students to complete most of it in class or to assign parts of it to be completed outside of class. Teacher should refer to the *Is My Model Working* project pages that are included as an attachment. Also attached is a power point *Is My Model Working*** PPT **that can be used by the teacher in the classroom each day as new parts of the project are started.

Day 0. 10 minute Formative Assessment. Teacher will give students a scatter plot and ask them to find the equation for the line of best fit and give an explanation of the slope and *y*-intercept in context of the data.

Day 1. 15 minute project introduction. Teacher will introduce the project as an opportunity for students to study data around them. Students will be asked to choose quantitative data pair ideas from a list (see project handout and examples below) or to use their own idea for data pairs. (Note: The data collection could be done in class but only if data pairs are restricted to data that students can get from classmates, or the Internet, if available in classroom.)

Examples from project handout:

- Shoe size and height in inches for 20 friends (must be same sex because of differences in shoe sizes)
- Weight bench-pressed and height in inches of 20 friends
- Miles from home and time getting to school for 20 friends

Homework. Data collection: Students need to choose their data idea and then collect 20 data pairs from chosen sources. Teacher should make suggestions but let students be responsible for finding their data. Students should enter their collected data in the table in the project handout.

Day 2. 10 minutes to check on student data. Students now need to randomly select two of their points to be saved for the last part of project. They will be used to evaluate the predication equation.

To randomly select two points of the 20, teacher could have a container with the numbers 1-20 on slips of paper. This container can be passed around the room with each student drawing and recording two numbers. These will be the points that will be saved until last section of project. Students need to remember to return the numbers they chose to the container and pass it to next student.

If teacher prefers, a random number generator on a calculator or computer could be used.

Teachers, should remind students how to set up their scatter plot graph. Emphasize that this is a first quadrant graph. Why? (Because domain and range of data are positive numbers.) Students should be advised to set up their units on the *x*-axis and the *y-*axis so that the majority of the graph is used. Why? (Because spreading out the points will make finding the line of best fit easier and allow the students to see the trend of the data.) Students should be reminded how to choose and/or show unit breaks in graphs.

Teacher can use the attached *Is My Model Working ***PPT **with prepared sample or take sample data from one of the students to review with the class how to choose an appropriate scale for each axis. Teacher should emphasize that students are to graph only 18 points. Teacher could review again how to find a good line of best fit.

Classwork or Homework: Students should complete their scatter plots using their 18 points. The points should be plotted on the supplied graph in the project pages. Students should then scrutinize their graphs and draw in a line of best fit. (10-15 minutes)

Day 3. 15-20 minutes for teacher to check on the students' individual scatter plots with line of best fit. Then teacher should model finding the equation of the line of best fit using two points on the line. *Is My Model Working ***PPT **example can be used or some data from a student in class. Mention that the project pages have an area for this work to be shown.

Teacher should continue discussion giving an interpretation of the slope and *y*-intercept for the students' best fit line. The teacher should remind the students to use appropriate units from their data for the slope and *y*-intercept. Also discuss whether or not the *y*-intercept is always meaningful. This should lead to a discussion of reasonable domain.

Classwork or Homework: Students should find an equation for their line of best fit and write full sentence interpretations of their slope and *y*-intercept. Student work should be recorded on the project pages. (15-20 minutes)

Day 4. 15-20 minutes. Teacher should check to see if the students have been successful in finding the equation of the line of best fit and in evaluating their slope and *y*-intercept. Since it is time consuming to check every step, suggest that seat partners check each other.

After this check, teacher will help students to determine whether or not their line of best fit is a good prediction equation. This will be done by looking at the residuals, i.e., the differences between the corresponding collected or observed *y* values and those predicted by the line of best fit. The term residual may be a new word.

Definition: Residual = Observed Value - Predicted Value. Note that each data point has a residual and are sometimes represented by a residual plot.

Teacher should explain that this is why the two random data pairs were saved. Teacher could model this with a student's sample data and their line of best fit, or use prepared example in *Is My Model Working PPT.* Teacher should have the students plug in the *x* values for the extra two points into the prediction equation, then subtract the results from the collected (or observed) *y* values from these points. These differences are the residuals. The project page is set up to help students do this calculation.

Teacher needs to help students understand how the residuals provides information regarding the consistency of their data. If the differences are small in context of the data then the line of best fit appears to be a good prediction equation or model. If the residuals are large in comparison to the context of the data then the line of best fit is not a good prediction equation. If one residual is small and the other large then no conclusion can be made at this time other than that more data should be collected to make a conclusion. (The size of the residuals can vary in context of the data, e.g., if the context is students' weight, 5-8 pounds would be a small difference but over 15 pounds would be a large difference.)

Classwork or Homework: Students should find their residuals and write an evaluation or conclusion determining whether or not their line of best fit is a good predication equation or model. This should be entered into the project paper.

Students now need to check to make sure that all of their project parts are complete and neatly presented so that it can be turned in.

Day 5. 15-20 minutes. Students are to turn in their completed projects. Teacher may choose a few students (or students can volunteer) to present details of their project and what they learned. For closure, students as a group should come up with characteristics of a good model.

##### Summative Assessment

The summative assessment will be the successful completion of the project with emphasis on valid conclusions made by the student concerning the linearity of their chosen data.

Here is suggested rubric for the project:

GRADING RUBRIC:

Part 1: T-chart with 20 well-labeled data pairs & sources up to 20 points____

(note: due on earlier date)

Part 2: Well-labeled correct graph with 18 points & best fit line

drawn in. up to 20 points____

Part 3: Correct work shown to find slope, *y*-int. & equation of line up to 20 points____

Part 4: Clear interpretations of slope & *y*-intercept in sentence form up to 20 points____

Part 5: Correct evaluation shown for extra two points and residual with clear conclusion

and explanation about prediction equation/model. up to 20 points____

Extra Credit: Neat work. up to 5 points ____

** Total (up to 105) _______**

** **

##### Feedback to Students

During this project activity, feedback will be given to students on a daily basis as they proceed through parts of the project. Teacher will discuss progress with the class and individually check on:

Part 1: Data collection. Teacher will check to make sure that data is appropriate, e.g. expressed height in inches and don't mix boys and girls shoe sizes.

Part 2: Drawing of scatter plot. Have students labeled the graphs correctly? Did they choose appropriate axes' scales? Did they find a line of best fit using trend of data? Did they randomly take out two points to save for later?

Part 3: Calculation of line of best fit. Do students remember how to find slope and *y*-intercept? Did they find the correct prediction line or algebraic model? Ask students if the line equation that they found makes sense when looking at their graph, e.g. Is the slope positive? Will the *y*-intercept hit about where they think?

Part 4: Slope and *y*-intercept interpretation. Did students understand how to interpret these parameters? Can they put it in a sentence?

Part 5: Evaluation of the line of best fit to be used as a prediction equation or model. Did students find expected values and use with actual values to find residuals? Do they understand how to use residuals to make a conclusion about their prediction equation? Did they show appropriate work?

This check should take 10-15 minutes daily during the week of the project.