# Activities

• • • ##### Subject Area

• Math: Middle Grades Math: Algebraic Thinking
• Math: Algebra I: Data Analysis
• Math: Algebra I: Linear Functions

• ##### Author 6-8
9-12

45 Minutes

• ##### Device
• TI-Nspire™
• TI-Nspire™ CAS
• ##### Software

TI-Nspire™
TI-Nspire™ CAS

• ##### Accessories

Sensor - Voltage

• ##### Other Materials
5 same size 1.5 volt batteries (A, AAA, etc.),
ruler

## "Add Them Up" for TI-Nspire

#### Activity Overview

This activity (which is based on "Add Them Up" from EasyData Collection Activities) involves the use of TI-Nspire, Vernier Easy Link, and a Voltage sensor in order to have students graph a scatterplot and determine an equation of best fit based on collected data.

#### Before the Activity

Students should be familiar with the "Grab and Move" feature of the TI-Nspire. Inform students that when batteries are lined up in a series, the positive terminal of one battery touches the negative terminal of the next battery.

#### During the Activity

Students will begin with a new .tns document and will connect the voltage sensor and EasyLink to the TI-Nspire in order to determine the voltage of 1.5 volt batteries. As the voltage of successive batteries is measured, students create data points on a Lists and Spreadsheets page. Students then determine an equation of best fit for this data, then use a Quick Graph to find an equation of best fit by creating a moveable line, then by finding an appropriate linear regression equation.

The first page of the handout involves the steps required to collect the data. The second page consists of teacher notes for leading students through the analysis of the collected data. The third page consists of a student worksheet for recording data. Instead of the worksheet, teachers may choose to use the TI-Nspire exclusively by having students record their responses on a Notes page.

#### After the Activity

Through class discussion, determine if students have any questions regarding conducting the experiment, defining slope as rate of change, the meaning of the y-intercept based on the regression equation, and/or any discrepancies between the equation of best fit that they determine and the equations found by using the TI-Nspire.