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```

"MODEL"  y  =  a * d  +  b * x  +  c * z;

"INPUT"  n, m, n * [ z, d, x, y, r ],
o, < (o+1) * o : 2 > * [ correl element ],
s, s * ( t, t * [ estimate ],
t, < (t+1) * t : 2 > * [ covar element ],
n, n * ( 6 * [ residual element ] ) );

"OPTIONS"  1, 2, 3, 5(1), 7;

```
```Transformed data matrix
=======================

obs.no.      a           b           c           dep.var.

1          1.000      25.000       1.398       0.790
2          1.000      50.000       1.699       0.984
3          1.000      80.000       1.903       1.058
4          1.000     130.000       2.114       1.163
5          1.000     180.000       2.255       1.209
```
```Control information
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

a                          1.000000                 0.000000                 1.000000                 1.000000
b                         93.000000                62.409935                25.000000               180.000000
c                          1.873843                 0.339506                 1.397940                 2.255273
dep.var.                   1.040800                 0.165565                 0.790000                 1.209000

Number of observations :    5

Correlation matrix of the variables
===================================

a           b           c           dep.var.

a           1.000000
b               *       1.000000
c               *       0.962417    1.000000
dep.var.        *       0.929750    0.993099    1.000000

Multiple correlation coefficient     0.997712    (adjusted   0.995418)
================================

Proportion of variation explained    0.995429    (adjusted   0.990858)
=================================

Standard deviation of the error term              0.015831
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

a                     -0.0899819314             0.1198580224                 0.563607                 0.531119

b                     -0.0009361326             0.0004670057                 4.018189                 0.182887

c                      0.6499168512             0.0858477522                57.313607                 0.017004

Correlation matrix of the estimates
===================================

a           b           c

a           1.000000
b           0.929333    1.000000
c          -0.993392   -0.962417    1.000000

Analysis of variance
====================

source of                                                                                           right  tail
variation          df          sum of squares           mean square             F - ratio           probability

---------------------------------------------------------------------------------------------------------------

total               5                5.525970

---------------------------------------------------------------------------------------------------------------

mean                1                5.416323              5.416323          21612.954083              0.000000
regression          2                0.109146              0.054573            217.763834              0.004571
residual            2                0.000501              0.000251

---------------------------------------------------------------------------------------------------------------

regression null hypothesis :  b = c = 0
```
```Residual analysis
=================
standardized         studentized
obs.no.        observation        fitted value    standard deviation          residual            residual            residual

1            0.790000            0.795160            0.015180           -0.005160           -0.515329           -1.148688
2            0.984000            0.967401            0.009923            0.016599            1.657926            1.345799
3            1.058000            1.071978            0.011074           -0.013978           -1.396083           -1.235555
4            1.163000            1.162208            0.009381            0.000792            0.079079            0.062090
5            1.209000            1.207254            0.014570            0.001746            0.174407            0.282096

sum of residuals :    -0.000000

Upper bound for the right tail probability of the largest absolute studentized residual (no. 2) :   0.994142
```
```Control information  -  submodel  1
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

c           omitted

a                          1.000000                 0.000000                 1.000000                 1.000000
b                         93.000000                62.409935                25.000000               180.000000
dep.var.                   1.040800                 0.165565                 0.790000                 1.209000

Number of observations :    5

Multiple correlation coefficient     0.929750    (adjusted   0.905122)
================================

Proportion of variation explained    0.864435    (adjusted   0.819246)
=================================

Standard deviation of the error term              0.070390
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

a                      0.8114159135             0.0611679599               175.970168                 0.000926

b                      0.0024664955             0.0005639337                19.129543                 0.022114

Correlation matrix of the estimates
===================================

a           b

a           1.000000
b          -0.857407    1.000000

Analysis of variance
====================

source of                                                                                           right  tail
variation          df          sum of squares           mean square             F - ratio           probability

---------------------------------------------------------------------------------------------------------------

total               5                5.525970

---------------------------------------------------------------------------------------------------------------

mean                1                5.416323              5.416323           1093.153257              0.000061
regression          1                0.094782              0.094782             19.129543              0.022114
residual            3                0.014864              0.004955

---------------------------------------------------------------------------------------------------------------

reduction          1                0.014363              0.014363             57.313607              0.017004

---------------------------------------------------------------------------------------------------------------

regression null hypothesis :  b = 0  (in the reduced model)

reduction null hypothesis :  c = 0  (in the original model)
```
```Residual analysis
=================
standardized         studentized
obs.no.        observation        fitted value    standard deviation          residual            residual            residual

1            0.790000            0.873078            0.049613           -0.083078           -1.523703           -1.663802
2            0.984000            0.934741            0.039736            0.049259            0.903443            0.847813
3            1.058000            1.008736            0.032322            0.049264            0.903537            0.787846
4            1.163000            1.132060            0.037767            0.030940            0.567451            0.520864
5            1.209000            1.255385            0.058293           -0.046385           -0.850729           -1.175640

sum of residuals :     0.000000

Upper bound for the right tail probability of the largest absolute studentized residual (no. 1) :   0.197018

End of job :  1
```
```

"MODEL"   available  =  beta0  +  beta1 * inorganic  +  beta2 * organic;

"INPUT"  k, l, k * [ constant, inorganic, organic, available ],
l, < (l+1) * l : 2 > * [ correl element ],
r, r * ( u, u * [ estimate ],
u, < (u+1) * u : 2 > * [ covar element ],
k, k * ( 6 * [ residual element ] ) );

"OPTIONS" Transformed data matrix, Correlation matrix, Residual analysis;

```
```Transformed data matrix
=======================

obs.no.      beta0       beta1       beta2       dep.var.

1          1.000       0.400      53.000      64.000
2          1.000       0.400      23.000      60.000
3          1.000       3.100      19.000      71.000
4          1.000       0.600      34.000      61.000
5          1.000       4.700      24.000      54.000
6          1.000       1.700      65.000      77.000
7          1.000       9.400      44.000      81.000
8          1.000      10.100      31.000      93.000
9          1.000      11.600      29.000      93.000
10          1.000      12.600      58.000      51.000

11          1.000      10.900      37.000      76.000
12          1.000      23.100      46.000      96.000
13          1.000      23.100      50.000      77.000
14          1.000      21.600      44.000      93.000
15          1.000      23.100      56.000      95.000
16          1.000       1.900      36.000      54.000
17          1.000      26.800      58.000     168.000
18          1.000      29.900      51.000      99.000
```
```Control information
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

beta0                      1.000000                 0.000000                 1.000000                 1.000000
beta1                     11.944444                10.154583                 0.400000                29.900000
beta2                     42.111111                13.624756                19.000000                65.000000
dep.var.                  81.277778                26.996308                51.000000               168.000000

Number of observations :   18

Correlation matrix of the variables
===================================

beta0       beta1       beta2       dep.var.

beta0       1.000000
beta1           *       1.000000
beta2           *       0.461567    1.000000
dep.var.        *       0.693403    0.354466    1.000000

Multiple correlation coefficient     0.694487    (adjusted   0.642875)
================================

Proportion of variation explained    0.482313    (adjusted   0.413288)
=================================

Standard deviation of the error term             20.678399
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

beta0                 56.2510240854            16.3107373404                11.893610                 0.003581

beta1                  1.7897741162             0.5567434145                10.334424                 0.005787

beta2                  0.0866492500             0.4149429933                 0.043607                 0.837396

Correlation matrix of the estimates
===================================

beta0       beta1       beta2

beta0       1.000000
beta1       0.086771    1.000000
beta2      -0.883117   -0.461567    1.000000

Analysis of variance
====================

source of                                                                                           right  tail
variation          df          sum of squares           mean square             F - ratio           probability

---------------------------------------------------------------------------------------------------------------

total              18           131299.000000

---------------------------------------------------------------------------------------------------------------

mean                1           118909.388889         118909.388889            278.088058              0.000000
regression          2             5975.668532           2987.834266              6.987514              0.007170
residual           15             6413.942579            427.596172

---------------------------------------------------------------------------------------------------------------

regression null hypothesis :  beta1 = beta2 = 0
```
```Residual analysis
=================
standardized         studentized
obs.no.        observation        fitted value    standard deviation          residual            residual            residual

1           64.000000           61.559344           10.596613            2.440656            0.129295            0.137448
2           60.000000           58.959866            8.994436            1.040134            0.055101            0.055862
3           71.000000           63.445660            9.817069            7.554340            0.400194            0.415085
4           61.000000           60.270963            7.439813            0.729037            0.038621            0.037786
5           54.000000           66.742544            8.277594          -12.742544           -0.675041           -0.672453
6           77.000000           64.925841           14.017687           12.074159            0.639633            0.794248
7           81.000000           76.887468            5.234633            4.112532            0.217863            0.205577
8           93.000000           77.013869            6.457231           15.986131            0.846871            0.813778
9           93.000000           79.525232            7.240620           13.474768            0.713830            0.695677
10           51.000000           83.827834            8.070605          -32.827834           -1.739066           -1.724294

11           76.000000           78.965584            5.239553           -2.965584           -0.157103           -0.148253
12           96.000000          101.580672            7.461991           -5.580672           -0.295638           -0.289377
13           77.000000          101.927269            7.367271          -24.927269           -1.320530           -1.290133
14           93.000000           98.722712            7.026946           -5.722712           -0.303163           -0.294260
15           95.000000          102.447164            7.905720           -7.447164           -0.394516           -0.389751
16           54.000000           62.770968            6.954672           -8.770968           -0.464645           -0.450398
17          168.000000          109.242627            9.235282           58.757373            3.112692            3.175816
18           99.000000          114.184382           10.161448          -15.184382           -0.804398           -0.843133

sum of residuals :     0.000000

Upper bound for the right tail probability of the largest absolute studentized residual (no. 17) :   0.001810

End of job :  2
```
```

"MODEL"  surface = alfa + beta * rate + gamma * wheel + delta * visco;

"INPUT"	 n, m, n * [ const, rate, wheel, visco, surface ],
s, s * ( t, t * [ estimate ],
n, n * ( 6 * [ residual element ] ) );

"OPTIONS" Transformed data matrix, Correlation matrix, Residual analysis;

```
```Transformed data matrix
=======================

obs.no.      alfa        beta        gamma       delta       dep.var.

1          1.000       4.051       8.575       2.226       3.235
2          1.000       2.765       8.594       2.235       3.453
3          1.000       2.777       9.024       2.235       3.246
4          1.000       4.440       9.287       2.244       2.856
5          1.000       2.263       8.434       2.283       3.643
6          1.000       4.440       9.333       2.254       2.901
7          1.000       4.406       8.666       2.254       3.277
8          1.000       4.406       8.987       2.303       2.960
9          1.000       3.199       9.210       2.244       3.105
10          1.000       3.199       8.795       2.254       3.273

11          1.000       2.765       9.071       2.263       3.250
12          1.000       3.199       8.389       2.263       3.472
13          1.000       3.182       8.936       2.244       3.223
14          1.000       2.293       8.476       2.244       3.681
15          1.000       4.075       8.039       2.244       3.572
16          1.000       3.189       9.138       2.254       3.157
17          1.000       4.075       8.949       2.323       3.096
18          1.000       4.075       8.575       2.313       3.277
19          1.000       2.293       8.648       2.323       3.681
20          1.000       2.777       8.732       2.283       3.450

21          1.000       2.777       8.949       2.283       3.292
22          1.000       4.075       9.230       2.303       2.896
23          1.000       4.440       8.476       2.283       3.346
24          1.000       3.199       8.795       2.283       3.307
25          1.000       2.777       9.024       2.283       3.250
26          1.000       4.075       8.949       2.283       3.140
27          1.000       3.199       9.105       0.489       3.153
28          1.000       4.075       9.220       0.480       2.896
29          1.000       3.199       8.575       0.399       3.431
30          1.000       2.777       8.987       0.472       3.246

31          1.000       2.293       8.896       0.489       3.367
32          1.000       4.440       8.764       1.115       3.091
33          1.000       4.075       8.987       1.076       2.934
34          1.000       4.440       9.180       0.612       2.885
35          1.000       3.199       8.748       0.663       3.346
```
```Control information
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

alfa                       1.000000                 0.000000                 1.000000                 1.000000
beta                       3.454469                 0.748055                 2.263364                 4.439656
gamma                      8.849891                 0.298180                 8.039157                 9.332558
delta                      1.851332                 0.732791                 0.398986                 2.322788
dep.var.                   3.239746                 0.228501                 2.856470                 3.681351

Number of observations :   35

Correlation matrix of the variables
===================================

alfa        beta        gamma       delta       dep.var.

alfa        1.000000
beta            *       1.000000
gamma           *       0.181207    1.000000
delta           *       0.002140   -0.184788    1.000000
dep.var.        *      -0.680447   -0.811063    0.197582    1.000000

Multiple correlation coefficient     0.978154    (adjusted   0.976014)
================================

Proportion of variation explained    0.956785    (adjusted   0.952603)
=================================

Standard deviation of the error term              0.049746
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

alfa                   8.5161547705             0.2628811987              1049.465191                 0.000000

beta                  -0.1692742083             0.0116047180               212.770983                 0.000000

gamma                 -0.5346926136             0.0296232726               325.793413                 0.000000

delta                  0.0217758632             0.0118544683                 3.374323                 0.075824

Correlation matrix of the estimates
===================================

alfa        beta        gamma       delta

alfa        1.000000
beta        0.034862    1.000000
gamma      -0.984808   -0.184785    1.000000
delta      -0.265643   -0.036859    0.188293    1.000000

Analysis of variance
====================

source of                                                                                           right  tail
variation          df          sum of squares           mean square             F - ratio           probability

---------------------------------------------------------------------------------------------------------------

total              35              369.133526

---------------------------------------------------------------------------------------------------------------

mean                1              367.358289            367.358289         148444.886282              0.000000
regression          3                1.698522              0.566174            228.783777              0.000000
residual           31                0.076716              0.002475

---------------------------------------------------------------------------------------------------------------

regression null hypothesis :  beta = gamma = delta = 0
```
```Residual analysis
=================
standardized         studentized
obs.no.        observation        fitted value    standard deviation          residual            residual            residual

1            3.234749            3.293605            0.014471           -0.058856           -1.257138           -1.236599
2            3.453157            3.501612            0.013422           -0.048455           -1.034982           -1.011563
3            3.246491            3.269608            0.014359           -0.023117           -0.493769           -0.485355
4            2.856470            2.847656            0.018843            0.008814            0.188267            0.191448
5            3.642836            3.673238            0.018930           -0.030403           -0.649389           -0.660875
6            2.901422            2.823664            0.019745            0.077758            1.660861            1.702966
7            3.277145            3.185918            0.015933            0.091227            1.948567            1.935824
8            2.960105            3.015032            0.015004           -0.054926           -1.173202           -1.158055
9            3.104587            3.098805            0.015705            0.005782            0.123491            0.122484
10            3.273364            3.321185            0.010062           -0.047821           -1.021423           -0.981573

11            3.250374            3.247224            0.015359            0.003151            0.067294            0.066585
12            3.471966            3.538192            0.015827           -0.066226           -1.414548           -1.404229
13            3.222868            3.248424            0.010836           -0.025556           -0.545868           -0.526370
14            3.681351            3.644690            0.018075            0.036661            0.783071            0.791030
15            3.572346            3.576834            0.027207           -0.004488           -0.095864           -0.107766
16            3.157000            3.139466            0.014204            0.017534            0.374526            0.367787
17            3.095578            3.092069            0.012560            0.003508            0.074932            0.072882
18            3.277145            3.291563            0.014848           -0.014419           -0.307973           -0.303683
19            3.681351            3.554511            0.016812            0.126840            2.709233            2.709112
20            3.449988            3.426623            0.012525            0.023364            0.499047            0.485299

21            3.292126            3.310771            0.013578           -0.018645           -0.398240           -0.389586
22            2.895912            2.941291            0.016367           -0.045379           -0.969282           -0.965996
23            3.346389            3.282092            0.019265            0.064297            1.373353            1.401884
24            3.306887            3.321816            0.010222           -0.014929           -0.318878           -0.306648
25            3.250374            3.270650            0.014597           -0.020276           -0.433078           -0.426348
26            3.139833            3.091198            0.012345            0.048634            1.038804            1.009211
27            3.152736            3.116926            0.018870            0.035810            0.764892            0.778000
28            2.895912            2.906863            0.020483           -0.010951           -0.233917           -0.241572
29            3.430756            3.398086            0.021955            0.032670            0.697814            0.731865
30            3.246491            3.250894            0.019844           -0.004403           -0.094054           -0.096529

31            3.367296            3.382300            0.022304           -0.015004           -0.320487           -0.337434
32            3.091042            3.102835            0.017624           -0.011793           -0.251893           -0.253504
33            2.933857            3.044480            0.014266           -0.110623           -2.362858           -2.321236
34            2.884801            2.869558            0.020728            0.015243            0.325573            0.337059
35            3.346389            3.311411            0.017225            0.034978            0.747120            0.749494

sum of residuals :     0.000000

Upper bound for the right tail probability of the largest absolute studentized residual (no. 19) :   0.166067

End of job :  3
```