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Calculating the Least Squares Regression Line
Lecture 49 Secs Wed, Apr 20, 2005
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The Least Squares Regression Line
The equation of the regression line is y^ = a + bx. Thus, we need to find the coefficients a and b. The formulas are
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Example Consider again the data x y 2 3 5 9 6 12 16
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Method 1 Compute the means and deviations for x and y. x y x -x y -y
2 3 -3 -6 5 -2 -4 9 6 12 1 16 4 7 x = 5 y = 9
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Method 1 Compute the squared deviations, etc. x y 2 3 -3 -6 9 36 18 5
x –x y –y (x –x)2 (y –y)2 (x –x)(y –y) 2 3 -3 -6 9 36 18 5 -2 -4 4 16 8 6 12 1 7 49 28
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Method 1 Find the sums of the last three columns. x y 2 3 -3 -6 9 36
x –x y –y (x –x)2 (y –y)2 (x –x)(y –y) 2 3 -3 -6 9 36 18 5 -2 -4 4 16 8 6 12 1 7 49 28 30 110 57
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Method 1 Compute b: Then compute a:
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Method 2 Consider again the data x y 2 3 5 9 6 12 16
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Method 2 Compute x2, y2, and xy for each row. x y x2 y2 xy 2 3 4 9 6 5
25 15 81 45 12 36 144 72 16 256
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Method 2 Then find the sums of x, y, x2, y2, and xy. x y x2 y2 xy 2 3
4 9 6 5 25 15 81 45 12 36 144 72 16 256 x = 25 y = 45 x2 = 155 y2 = 515 xy = 282 25 45 155 515 282
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Method 2 Compute b: Then compute a:
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Example The second method is usually easier.
By either method, we get the equation y^ = x.
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TI-83 – Regression Line On the TI-83, we could use 2-Var Stats to get the basic summations. Then use the formulas for a and b. For our example, 2-Var Stats reports that n = 5 x = 25 x2 = 155 y = 45 y2 = 515 xy = 282
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TI-83 – Regression Line Or we can use the LinReg function.
Put the x values in L1 and the y values in L2. Select STAT > CALC > LinReg(a+bx). Press Enter. LinReg(a+bx) appears in the display. Enter L1, L2. Press Enter.
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TI-83 – Regression Line The following appear in the display.
The title LinReg. The equation y = a + bx. The value of a. The value of b. The value of r2 (to be discussed later). The value of r (to be discussed later).
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Let’s Do It! Let’s Do It! 13.3, p. 754 – Oil Change Data.
Use the TI-83!
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