Multi-Linear Regression Preview

HardHeat=a0·Wpc1+a1·Wpc2+a2·Wpc3+a3·Wpc4
Data-Table
 Wpc1Wpc2Wpc3Wpc4HardHeat
172666078.7
2129155274.3
31156820104.3
4113184787.6
575263395.9
61155922109.2
7371176102.7
8131224472.5
9254182293.1
102147426115.9
11140233483.8
121166912113.3
131068812109.4

Program validated. Ready to Solve.
# Example 31(b) - Multi-Linear Regression via origin
# Heat of Hardening
# Verified Solution: a1=2.18918, a2=1.15414, a3=0.753295 , a4=0.488545
# Ref: Comput Appl Eng Educ 17: 285, 1998

[
Wpc1 Wpc2 Wpc3 Wpc4 HardHeat
7 26 6 60 78.7
1 29 15 52 74.3
11 56 8 20 104.3
11 31 8 47 87.6
7 52 6 33 95.9
11 55 9 22 109.2
3 71 17 6 102.7
1 31 22 44 72.5
2 54 18 22 93.1
21 47 4 26 115.9
1 40 23 34 83.8
11 66 9 12 113.3
10 68 8 12 109.4
]

mlinfit Wpc1 Wpc2 Wpc3 Wpc4 HardHeat origin

Regression Model

y = a0 x1 + a1 x2 + a2 x3 + a3 x4

where y and xi map to:
HardHeat = a0 Wpc1 + a1 Wpc2 + a2 Wpc3 + a3 Wpc4

VariableValue95% confidence
a02.18917660.418269
a11.15413570.108233
a20.753294940.360111
a30.488545150.0934830

R²adjRmsdVariance
0.9806560.9742080.5568445.82252

Multilinear Regression Fit
Chart
Multilinear Regression HardHeat Residuals
Chart

Data Table

 Wpc1Wpc2Wpc3Wpc4HardHeatCalculated HardHeatResidual %
172666078.779.164242-0.5899%
2129155274.372.3628832.607%
31156820104.3104.50980-0.2012%
4113184787.688.847130-1.424%
575263395.995.981050-0.08452%
61155922109.2105.086053.767%
7371176102.7104.24845-1.508%
8131224472.576.035858-4.877%
9254182293.191.0089812.246%
102147426115.9115.93244-0.02799%
11140233483.882.2909221.801%
121166912113.3112.896090.3565%
131068812109.4112.261890.000%

Settings and Hints

 Name/SourceValueType
1 Independent variables 4 Setting
2 Sample data 13 Setting
3 Version 7.0.73 Setting
4 #@report_fix_digits = 8 Default (integer)
5 #@chart_size = 428,300 Default (array)
6 #@report_show_source = true Default (boolean)
7 #@report_show_header = false Default (boolean)
8 #@report_show_settings = true Default (boolean)
9 #@report_show_charts = true Default (boolean)
10 #@report_show_data_points = true Default (boolean)

Messages

 SeverityDescription
1Info-Infor- 5 Known vectors variables (Wpc1, Wpc2, Wpc3, Wpc4, HardHeat)
2Info-Infor- 0 Explicit expressions
3Info-Infor- Regression command: mlinfit Wpc1 Wpc2 Wpc3 Wpc4 HardHeat origin

Source

# Example 31(b) - Multi-Linear Regression via origin
# Heat of Hardening
# Verified Solution: a1=2.18918, a2=1.15414, a3=0.753295 , a4=0.488545
# Ref: Comput Appl Eng Educ 17: 285, 1998

[
Wpc1 Wpc2 Wpc3 Wpc4 HardHeat
7 26 6 60 78.7
1 29 15 52 74.3
11 56 8 20 104.3
11 31 8 47 87.6
7 52 6 33 95.9
11 55 9 22 109.2
3 71 17 6 102.7
1 31 22 44 72.5
2 54 18 22 93.1
21 47 4 26 115.9
1 40 23 34 83.8
11 66 9 12 113.3
10 68 8 12 109.4
]

mlinfit Wpc1 Wpc2 Wpc3 Wpc4 HardHeat origin