Minitab Analysis
Regression Analysis: IBI versus Area
The regression equation is
IBI = 52.9 + 0.460 Area
Predictor Coef SE Coef T P
Constant 52.923 4.484 11.80 0.000
Area 0.4602 0.1347 3.42 0.001
S = 16.5346 R-Sq = 19.9% R-Sq(adj) = 18.2%
Analysis of Variance
Source DF SS MS F P
Regression 1 3189.3 3189.3 11.67 0.001
Residual Error 47 12849.5 273.4
Total 48 16038.8
Unusual Observations
Obs Area IBI Fit SE Fit Residual St Resid 10 70.0 89.00 85.13 6.10 3.87 0.25 X 15 69.0 80.00 84.67 5.97 -4.67 -0.30 X 24 19.0 29.00 61.67 2.67 -32.67 -2.00R
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
Regression Analysis: IBI versus Forest
The regression equation is
IBI = 59.9 + 0.153 Forest
Predictor Coef SE Coef T P
Constant 59.907 4.040 14.83 0.000
Forest 0.15313 0.07972 1.92 0.061
S = 17.7880 R-Sq = 7.3% R-Sq(adj) = 5.3%
Analysis of Variance
Source DF SS MS F P
Regression 1 1167.4 1167.4 3.69 0.061
Residual Error 47 14871.5 316.4
Total 48 16038.8
Unusual Observations
Obs Forest IBI Fit SE Fit Residual St Resid 23 32 29.00 64.81 2.61 -35.81 -2.04R 24 33 29.00 64.96 2.59 -35.96 -2.04R
Regression Analysis: IBI versus Forest
The regression equation is
IBI = 59.9 + 0.153 Forest
Predictor Coef SE Coef T P
Constant 59.907 4.040 14.83 0.000
Forest 0.15313 0.07972 1.92 0.061
S = 17.7880 R-Sq = 7.3% R-Sq(adj) = 5.3%
Analysis of Variance
Source DF SS MS F P
Regression 1
The regression equation is
IBI = 52.9 + 0.460 Area
Predictor Coef SE Coef T P
Constant 52.923 4.484 11.80 0.000
Area 0.4602 0.1347 3.42 0.001
S = 16.5346 R-Sq = 19.9% R-Sq(adj) = 18.2%
Analysis of Variance
Source DF SS MS F P
Regression 1 3189.3 3189.3 11.67 0.001
Residual Error 47 12849.5 273.4
Total 48 16038.8
Unusual Observations
Obs Area IBI Fit SE Fit Residual St Resid 10 70.0 89.00 85.13 6.10 3.87 0.25 X 15 69.0 80.00 84.67 5.97 -4.67 -0.30 X 24 19.0 29.00 61.67 2.67 -32.67 -2.00R
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
Regression Analysis: IBI versus Forest
The regression equation is
IBI = 59.9 + 0.153 Forest
Predictor Coef SE Coef T P
Constant 59.907 4.040 14.83 0.000
Forest 0.15313 0.07972 1.92 0.061
S = 17.7880 R-Sq = 7.3% R-Sq(adj) = 5.3%
Analysis of Variance
Source DF SS MS F P
Regression 1 1167.4 1167.4 3.69 0.061
Residual Error 47 14871.5 316.4
Total 48 16038.8
Unusual Observations
Obs Forest IBI Fit SE Fit Residual St Resid 23 32 29.00 64.81 2.61 -35.81 -2.04R 24 33 29.00 64.96 2.59 -35.96 -2.04R
Regression Analysis: IBI versus Forest
The regression equation is
IBI = 59.9 + 0.153 Forest
Predictor Coef SE Coef T P
Constant 59.907 4.040 14.83 0.000
Forest 0.15313 0.07972 1.92 0.061
S = 17.7880 R-Sq = 7.3% R-Sq(adj) = 5.3%
Analysis of Variance
Source DF SS MS F P
Regression 1