Results: wheatear.sas

wheatear regression example

tcell mean for input into estimate command in proc glm

The Print Procedure

Data Set WORK.NEW0

Obs tcellmean
1 0.32395

The SGScatter Procedure

The SGScatter Procedure

The SGScatter Procedure

wheatear regression example

regression of stone mass on tcell response

The GLM Procedure

The GLM Procedure

Data

Number of Observations

Number of Observations Read 21
Number of Observations Used 21

wheatear regression example

regression of stone mass on tcell response

The GLM Procedure

 

Dependent Variable: mass

Analysis of Variance

mass

Overall ANOVA

Source DF Sum of Squares Mean Square F Value Pr > F
Model 1 19.33949354 19.33949354 9.51 0.0061
Error 19 38.62662075 2.03298004    
Corrected Total 20 57.96611429      

Fit Statistics

R-Square Coeff Var Root MSE mass Mean
0.333634 19.79136 1.425826 7.204286

Type I Model ANOVA

Source DF Type I SS Mean Square F Value Pr > F
tcell 1 19.33949354 19.33949354 9.51 0.0061

Type II Model ANOVA

Source DF Type II SS Mean Square F Value Pr > F
tcell 1 19.33949354 19.33949354 9.51 0.0061

Estimates

Parameter Estimate Standard
Error
t Value Pr > |t| 95% Confidence Limits
intercept 3.9112702 1.11208441 3.52 0.0023 1.5836507 6.2388896
slope 10.1651222 3.29576786 3.08 0.0061 3.2670008 17.0632436
mean 7.2042615 0.31114076 23.15 <.0001 6.5530364 7.8554866

Solution

Parameter Estimate Standard
Error
t Value Pr > |t| 95% Confidence Limits
Intercept 3.91127017 1.11208441 3.52 0.0023 1.58365074 6.23888959
tcell 10.16512222 3.29576786 3.08 0.0061 3.26700082 17.06324362

wheatear regression example

regression of stone mass on tcell response

The GLM Procedure

Predictions

Values

Observation   Observed Predicted Residual 95% Confidence Limits for Mean Predicted Value
1   3.33000000 6.47288097 -3.14288097 5.65407464 7.29168730
2   4.62000000 6.58469731 -1.96469731 5.80953401 7.35986062
3   5.43000000 6.46271585 -1.03271585 5.63970979 7.28572190
4   5.73000000 6.46271585 -0.73271585 5.63970979 7.28572190
5   6.12000000 5.77148753 0.34851247 4.60124212 6.94173295
6   6.29000000 6.07644120 0.21355880 5.07151601 7.08136639
7   6.45000000 7.28609075 -0.83609075 6.63250382 7.93967767
8   6.51000000 5.97478998 0.53521002 4.91638345 7.03319651
9   6.65000000 6.47288097 0.17711903 5.65407464 7.29168730
10   6.75000000 7.38774197 -0.63774197 6.72472383 8.05076010
11   6.81000000 8.69904273 -1.88904273 7.49363626 9.90444921
12   7.56000000 8.29243785 -0.73243785 7.30787233 9.27700336
13   7.83000000 7.08278830 0.74721170 6.42636469 7.73921192
14   8.02000000 7.00146732 1.01853268 6.33585690 7.66707774
15   8.06000000 7.67236539 0.38763461 6.94780303 8.39692775
16   8.18000000 7.78418173 0.39581827 7.02329198 8.54507149
17   9.08000000 8.28227272 0.79772728 7.30287019 9.26167525
18   9.15000000 8.28227272 0.86772728 7.30287019 9.26167525
19   9.35000000 6.07644120 3.27355880 5.07151601 7.08136639
20   9.42000000 9.07515226 0.34484774 7.64829043 10.50201408
21   9.95000000 8.08913540 1.86086460 7.20332933 8.97494147

Information

Sum of Residuals -0.00000000
Sum of Squared Residuals 38.62662075
Sum of Squared Residuals - Error SS 0.00000000
PRESS Statistic 47.35583810
First Order Autocorrelation 0.44282434
Durbin-Watson D 0.76898024

Residual Plots

tcell

Plot of Residual by tcell for mass

Fit Plot

Fit Plot for mass by tcell

wheatear regression example

regression of stone mass on tcell response

The Print Procedure

Data Set WORK.NEW

Obs mass tcell clml clmu clpl clpu yhat resid
1 3.33 0.252 5.65407 7.2917 3.37830 9.5675 6.47288 -3.14288
2 4.62 0.263 5.80953 7.3599 3.50138 9.6680 6.58470 -1.96470
3 5.43 0.251 5.63971 7.2857 3.36702 9.5584 6.46272 -1.03272
4 5.73 0.251 5.63971 7.2857 3.36702 9.5584 6.46272 -0.73272
5 6.12 0.183 4.60124 6.9417 2.56595 8.9770 5.77149 0.34851
6 6.29 0.213 5.07152 7.0814 2.92750 9.2254 6.07644 0.21356
7 6.45 0.332 6.63250 7.9397 4.23107 10.3411 7.28609 -0.83609
8 6.51 0.203 4.91638 7.0332 2.80837 9.1412 5.97479 0.53521
9 6.65 0.252 5.65407 7.2917 3.37830 9.5675 6.47288 0.17712
10 6.75 0.342 6.72472 8.0508 4.33069 10.4448 7.38774 -0.63774
11 6.81 0.471 7.49364 9.9044 5.48051 11.9176 8.69904 -1.88904
12 7.56 0.431 7.30787 9.2770 5.14993 11.4349 8.29244 -0.73244
13 7.83 0.312 6.42636 7.7392 4.02716 10.1384 7.08279 0.74721
14 8.02 0.304 6.33586 7.6671 3.94385 10.0591 7.00147 1.01853
15 8.06 0.370 6.94780 8.3969 4.60138 10.7434 7.67237 0.38763
16 8.18 0.381 7.02329 8.5451 4.70442 10.8639 7.78418 0.39582
17 9.08 0.430 7.30287 9.2617 5.14138 11.4232 8.28227 0.79773
18 9.15 0.430 7.30287 9.2617 5.14138 11.4232 8.28227 0.86773
19 9.35 0.213 5.07152 7.0814 2.92750 9.2254 6.07644 3.27356
20 9.42 0.508 7.64829 10.5020 5.76730 12.3830 9.07515 0.34485
21 9.95 0.411 7.20333 8.9749 4.97616 11.2021 8.08914 1.86086

wheatear regression example

descriptive statistics for residuals

The UNIVARIATE Procedure

Variable: resid

The Univariate Procedure

resid

Basic Measures of Location and Variability

Basic Statistical Measures
Location Variability
Mean 0.000000 Std Deviation 1.38972
Median 0.344848 Variance 1.93133
Mode . Range 6.41644
    Interquartile Range 1.47993

Tests For Normality

Tests for Normality
Test Statistic p Value
Shapiro-Wilk W 0.957292 Pr < W 0.4633
Kolmogorov-Smirnov D 0.169755 Pr > D 0.1128
Cramer-von Mises W-Sq 0.092397 Pr > W-Sq 0.1362
Anderson-Darling A-Sq 0.503659 Pr > A-Sq 0.1904

Quantiles

Quantiles (Definition 5)
Level Quantile
100% Max 3.273559
99% 3.273559
95% 1.860865
90% 1.018533
75% Q3 0.747212
50% Median 0.344848
25% Q1 -0.732716
10% -1.889043
5% -1.964697
1% -3.142881
0% Min -3.142881

Extreme Values

Extreme Values
Lowest Highest
Order Value Order Value
1 -3.142881 17 0.797727
2 -1.964697 18 0.867727
3 -1.889043 19 1.018533
4 -1.032716 20 1.860865
5 -0.836091 21 3.273559

wheatear regression example

descriptive statistics for residuals

The UNIVARIATE Procedure

Q-Q Plot 1

Panel 1

Q-Q plot for resid