While this support activity is designed for a face-to-face, synchronous delivery, it should be noted that supporting text and interactive examples have been embedded in the digital assignment page to assist asynchronous or hybrid course delivery and to be made more accessible to students performing make-up work.

Notes for synchronous active-learning delivery

Use this corequisite support activity to prepare students to model bivariate data using linear equations.

Begin the support activity by having students watch a video about Kai’s journey. Here is the link to the video: https://www.youtube.com/watch?v=-HFFSYcEMCI. 

Questions 1 and 2 are designed to help students process their emotions related to the video. The first question is optional, but the second question can be used to develop students’ perseverance skills.

Students may work together to complete the remainder of the questions.

In Question 3, make sure students read carefully and understand the column for Kai’s weight should decrease by two pounds per week.

In Question 4, make sure students are labeling their axes appropriately.

• Guide students to use the number of weeks as the independent variable and weight as the dependent variable.
• You can do this in the context of the situation since the goal is to predict weight based on weeks in the program.
• Emphasize that in statistics and mathematics, conventionally, the independent variable is represented on the horizontal axis and the dependent variable is represented on the vertical axis.

In Question 8, consider having a few students describe their mathematical processes by asking: “How are you arriving at your answers?” Use student answers to emphasize the underlying mathematical operations rather than going to an abstract notion of [latex]y=mx+b[/latex].

In Question 9, allow students choose any variables they would like, as long as they define the variables appropriately. Question 10 will connect the variables students define in Question 9 to [latex]x[/latex] and [latex]y[/latex] variables typically used in statistics and in the DCMP Data Analysis Tools.

Wrap up by emphasizing that in statistics, independent variables are called explanatory variables and dependent variables are called response variables.