# Example 14 - Simple multiple linear regression
# y = a0 + a1*x1 + a2*x2
# Verified Solution: a0 =360.836, a1 = -3.75246 a2=-0.084265
[
y x1 x2
293 1.61 851
230 15.5 820
172 22 1058
91 45 1201
125 33 1357
125 40 1115
]
# mlinfit <x1> <x2> <x3> [...] <y> [origin]
mlinfit x1 x2 y
y = a0 + a1x1 + a2x2
| Variable |
Value |
95% confidence |
| a0 |
360.83566 |
118.07555 |
| a1 |
-3.7524613 |
1.7739996 |
| a2 |
-0.08426503 |
0.14031331 |
| R^2 |
R^2adj |
Rmsd |
Variance |
| 0.9835209 |
0.9725349 |
3.642287 |
159.1951 |
Regression Plot

Residuals Plot

Source data points and calculated data points
| |
x1 |
x2 |
y |
y calc |
Delta y |
| 1 |
1.61 |
851 |
293 |
283.08465 |
9.9153492 |
| 2 |
15.5 |
820 |
230 |
233.57518 |
-3.575179 |
| 3 |
22 |
1058 |
172 |
189.1291 |
-17.129103 |
| 4 |
45 |
1201 |
91 |
90.772592 |
0.22740759 |
| 5 |
33 |
1357 |
125 |
122.65678 |
2.3432168 |
| 6 |
40 |
1115 |
125 |
116.78169 |
8.2183081 |
General
Number of independent variables = 2
Regression including a free parameter
Number of observations = 6