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LinearRegression - Using Your TI-83/84 Calculator Linear...

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Using Your TI-83/84 Calculator: Linear Correlation and Regression Elementary Statistics Dr. Laura Schultz This handout describes how to use your calculator for various linear correlation and regression applications. For illustration purposes, we will work with a data set consisting of the winning men’s Olympic high jump heights (in inches) paired with the years those heights were attained. To simplify the regression equation, I have coded the Olympic year to be zero in 1900. You can find this data set in the Appendix at the end of this handout. 1. Before we can get started, you will need to enter the men’s Olympic high jump data into your calculator. We will be using this data set for several different applications, so it will be helpful to enter the data into named lists. Press Se . Insert a list by highlighting L 1 and pressing `d . Name this list OLYR and proceed to enter the year-code data into this list. Insert another list named JUMP and enter the high-jump height data into this list. Check over your lists to make sure you didn’t enter any incorrect data values. Note that each OLYR value must be paired with the corresponding high JUMP height for that year. 2. Generating a Scatterplot. To get a sense of the data, start by generating a scatterplot. Press `! to access the , menu. Make sure all the plots except Plot1 are turned off, and then press 1 . Select the first Type of plot. At the Xlist prompt, enter the name of the list containing the predictor variable; this variable will be assigned to the x -axis of the plot. For this example, the Xlist is OLYR . Enter the name of the response variable at the Ylist prompt; the values in this list will be plotted on the y -axis. The Ylist for this example is JUMP . 3. Press #9 to view the scatterplot. There should be no line drawn through the points on your plot; if there is a line, you will need to press ! and make sure all the equations are empty for Plot1 . (Select any equation you need to clear and press C .) What can you tell from the scatterplot? Does there appear to be a linear correlation between OLYR and JUMP ? If so, is it positive or negative? How strong does the correlation appear to be? 4. The next step is to find the linear correlation coefficient ( r ) and determine whether there is a significant linear correlation between our two variables. The LinRegTTest function on your calculator provides “one-stop shopping” for answering these and other questions relating to linear correlation and regression. Press S and scroll right to the TESTS menu. Scroll down to LinRegTTest and press e . ( Note: This is menu-item F on a TI-84 calculator, but it is E on a TI-83 calculator. ) Copyright © 2007 by Laura Schultz. All rights reserved. Page 1 of 5
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