Module 2  Lines  
Introduction  Lesson 1  Lesson 2  Lesson 3  Self Test  
Lesson 2.2: Scatter Plots and Linear Regression  
In this lesson you will enter data, create a scatter plot of the data, find the regression line that best fits the data, and display the regression line along with the scatter plot. The CarValue Example To illustrate the procedure for creating a scatter plot of a data set and the regression equation that best models the data, the relationship between a car's age and its value will be explored. The following example will guide you to
Clearing the Lists Before a scatter plot can be displayed or a regression equation can be created, the data must be entered into lists in the STAT List editor.
We want the List Editor to contain the lists L1L6. If they aren't there, you need to reset the list names in the editor using the following Tech Tip.
If the list L1 is not empty,
If other lists are not empty,
Creating the Data Lists The following values (selling prices) for different ages of a particular model of car were taken from the classified ads of a newspaper. Enter the data into the lists L1 and L2 by following the directions below. The ages will be entered in the list L1 and the corresponding prices will be entered in the list L2.
Move the cursor to L2 with the right arrow key
and enter the values for "Price".
Displaying a Scatter Plot of the Data You can illustrate the data with a scatter plot displayed on the Graph screen. The process entails
Defining the Plot
Define the scatter plot in Plot1. Details of the procedure are outlined below. Plot1 should now be defined as shown above. Set Up the Viewing Window By looking at the data, an appropriate Viewing window for the scatter plot is [1, 8, 1] x [3000, 15000, 1000].
Display the Scatter Plot
The Linear Regression Equation The TI83 has a feature that can be used to find the line that best fits the data. Such a line is called the "regression line" or "line of best fit." The following procedure
You need to identify which list contains the xvalues, which list contains the yvalues, and where you would like to store the regression equation.
The equation is generated, displayed on the Home screen, and stored in Y1 in the Y= editor. Home Screen The Regression Equation in the Y= Editor The linear equation that best fits the data is approximately where x is the age of the car and y is its value.
MedMed The MedMed (medianmedian) feature in the STAT CALC menu fits the model equation y = ax + b to the data using the medianmedian line technique instead of the leastsquares line of best fit technique used by linear regression. MedMed displays values for a (slope) and b (yintercept). The syntax for the MedMed command is the same as the syntax for the LinReg(ax+b) command. 2.2.1 Perform MedMed on the carvalue data in this lesson and compare the resultant equation with the equation found using LinReg(ax+b), y = 1478x + 13,906. Click here for the answer. 

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