Linear Models and Scatter Plots

# Linear Models and Scatter Plots -

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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>2.6 - Exploring Data: Linear Models and Scatter Plots</title> <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1" /> <link href=". ./m116.css" rel="stylesheet" type="text/css" /> </head> <body> <h1>2.6 - Exploring Data: Linear Models and Scatter Plots</h1> <p>This section ties in heavily with the notes for a <a href=". ./. ./m170/">statistics class</a>. In particular, look at the <a href=". ./. ./. ./ti82/ti-lists.html">Introduction to Statistics and Lists on the TI82</a> and <a href=". ./. ./. ./ti82/ti-plot3.html">Scatter Plots and Regression Lines on the TI82</a>. With that said, I will try to convey most of that information here, also.</p> <p>I have included notes for the TI82, TI83, and TI85 calculators. I don't normally do the TI85, but the statistics mode on it is fairly difficult to grasp. I do not have notes on how to use any of the other calculators, like the Casio or Sharp. If you would rather see all of the notes for your calculator in one location, then see the lecture notes for either the <a href="models82.html">TI82 / TI83</a> or the <a href="models85.html">TI85</a>. Everything here is included there, so you only need to print one or the other.</p> <h3>TI83 Users Only</h3> <p>There is a correlation coefficient which is mentioned in the book. By default, the TI83 does not give this to you. You can enable it (you only need to do this once, and then it's done forever more until you lose power or reset your calculator) by going [Catalog] (2<sup>nd</sup> zero). Then, scroll down to <strong>DiagnosticOn</strong> (hit D [the calculator is already in alpha mode, so just press the inverse key] to get close quickly) and press enter twice until the calculator says Done.</p> <h2>Correlation and Regression</h2> <p>The Linear Correlation Coefficient (r) is a measure of the strength and direction of a relationship between two variables. If the y gets larger when the x gets larger, the coefficient is positive and if the y gets smaller when the x gets larger, the coefficient is negative. If there is no linear relationship between the two variables, then the coefficient is zero. If all the data exactly lies on a line, then it is called perfect correlation and the value will either be 1 or -1. The closer the value is to 1 or -1, the closer the points are to the line and the stronger the linear relationship. The same concept applies for other types of regression (the TI82, TI83, and TI85 will do linear, logarithmic, exponential, power, quadratic, cubic, and quartic regression). </p>

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## This note was uploaded on 10/18/2011 for the course MAT 1033 taught by Professor Brown during the Spring '10 term at Valencia.

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Linear Models and Scatter Plots -

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