Compute the least squares regression line for the data in Exercise 2 of Chapter 10, Section 2 “The Linear Correlation Coefficient”. data: x 0 2 3 6 9 y 0 3 3 4 8
Solution:
From the data
X | Y | XY | X^2 | Y^2 |
0 | 0 | 0 | 0 | 0 |
2 | 3 | 6 | 4 | 9 |
3 | 3 | 9 | 9 | 9 |
6 | 4 | 24 | 36 | 16 |
9 | 8 | 72 | 81 | 64 |
n | 5 |
sum(XY) | 111.00 |
sum(X) | 20.00 |
sum(Y) | 18.00 |
sum(X^2) | 130.00 |
sum(Y^2) | 98.00 |
Numerator | 195.00 |
Denominator | 203.72 |
r | 0.9572 |
r square | 0.9163 |
Xbar(mean) | 4.0000 |
Ybar(mean) | 3.6000 |
SD(X) | 3.1623 |
SD(Y) | 2.5768 |
b | 0.7800 |
a | 0.4800 |
The Linear Correlation Coefficient = r = 0.9572
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