S; R-sq ; R-sq(adj) ;R-sq(pred)
* ; 100.00% ; * ; *Coefficients
Term ; Coef; Coef ; T-Value; P-Value ; VIF
Constant ; 0.07526 ; * ; *; *;
Hardware EV ; 0.3593 ; * ; * ; *; 230.84
Mechanical EV ; 0.2933 ; * ; *; * ; 75.04
Production EV ; 0.1455 ; * ; * ; * ; 252.27
Firmware EV ; -0.3805 ; * ; * ; * ; 38.53
Note> i need the values in the place of *.
There are insufficient degrees of freedom for the calculations (including the standard deviation and the model term p-values). If this is from a DOE, you might need to augment your design with some additional runs. See Minitab support note http://support.minitab.com/en-us/minitab/17/topic-library/modeling-statistics/doe/basics/f--and-p-values-that-are-shown-as-asterisks/
Typical successful Minitab regression output will show the P-values and standard deviation (as well as other statistics) in the ANOVA table and model summary as shown below:
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 0.03728 0.037275 100.74 0.000
Temperature 1 0.03728 0.037275 100.74 0.000
Error 98 0.03626 0.000370
Lack-of-Fit 47 0.01698 0.000361 0.96 0.561
Pure Error 51 0.01928 0.000378
Total 99 0.07354
Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.0192354 50.69% 50.19% 48.55%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 100.234 0.022 4475.56 0.000
Temperature -0.01073 0.00107 -10.04 0.000 1.00
Hope this is useful to you!