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### Econ.3640.33.Spring.2007

Course: ECON 3640, Fall 2008
School: Utah
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Economics 3640-001 Lecture 33: Ch.9 Simple Linear Regression 9.2 Fitting the Model: The &lt;a href=&quot;/keyword/least-squares/&quot; &gt;least squares&lt;/a&gt; Approach 1. Plot the sample data in a scattergram. 2. If you see a general tendency for y to increase (or decrease) as x increases, you may draw a line through the sample data points. 3. Note the extent to which the data points...

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Economics 3640-001 Lecture 33: Ch.9 Simple Linear Regression 9.2 Fitting the Model: The <a href="/keyword/least-squares/" >least squares</a> Approach 1. Plot the sample data in a scattergram. 2. If you see a general tendency for y to increase (or decrease) as x increases, you may draw a line through the sample data points. 3. Note the extent to which the data points deviate from the line. These deviations, or errors of prediction, are the vertical distances between observed and predicted values. Instructor: Sanghoon Lee 4. Now, we want to find a line for which the SSE is a minimum. This line is called the <a href="/keyword/least-squares/" >least squares</a> line, or the regression line. Def. 9.1 The <a href="/keyword/least-squares/" >least squares</a> line is one that has the following two properties: 1. the sum of the errors (SE) equals 0 2. the sum of squared errors (SSE) is smaller than that for any other straight-line model Ex. 9.16 Construct a scattergram for the data in the following table. x .5 1 1.5 y 2 1 3 a. Plot the following two lines on your scattergram: y = 3 x and y = 1 + x. b. Which of these lines would you choose to characterize the relationship between x and y? c. Show that the sum of errors for both of these lines equals 0. d. Which of ...

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