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```***********************************
*  Example  1  originates from:   *
*  reference [4],  page 472, 479  *
***********************************

"Model"   y  =  c * Log (x)  +  a  +  b * x;

"Input"   5 * ([x], 10 * [y]);

"Options" Transformed data matrix, Correlation matrix,
Residual analysis, Process submodels (1, 2);

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

obs.no.      c           a           b           dep.var.     repeats

1          1.398       1.000      25.000       0.790      10.000
2          1.699       1.000      50.000       0.984      10.000
3          1.903       1.000      80.000       1.058      10.000
4          2.114       1.000     130.000       1.163      10.000
5          2.255       1.000     180.000       1.209      10.000
```
```Control information
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

c                          1.873843                 0.306746                 1.397940                 2.255273
a                          1.000000                 0.000000                 1.000000                 1.000000
b                         93.000000                56.387870                25.000000               180.000000
dep.var.                   1.040800                 0.163655                 0.670000                 1.330000

Number of observations :    5

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

c           a           b           dep.var.

c           1.000000
a               *       1.000000
b           0.962417        *       1.000000
dep.var.    0.907742        *       0.849838    1.000000

Multiple correlation coefficient     0.911959    (adjusted   0.908023)
================================

Proportion of variation explained    0.831669    (adjusted   0.824506)
=================================

Standard deviation of the error term              0.068558
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

c                      0.6499168512             0.1175695440                30.558070                 0.000001

a                     -0.0899819314             0.1641470240                 0.300500                 0.586163

b                     -0.0009361326             0.0006395700                 2.142390                 0.149935

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

c           a           b

c           1.000000
a          -0.993392    1.000000
b          -0.962417    0.929333    1.000000

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

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

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

total              50               55.475600

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

mean                1               54.163232             54.163232          11523.444701              0.000000
regression          2                1.091456              0.545728            116.105776              0.000000
residual           47                0.220912              0.004700

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

lack of fit        2                0.005012              0.002506              0.522336              0.596686
pure error        45                0.215900              0.004798

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

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

1            0.790000            0.795160            0.020789           -0.005160           -0.118992           -0.078976
2            0.984000            0.967401            0.013590            0.016599            0.382824            0.247021
3            1.058000            1.071978            0.015165           -0.013978           -0.322363           -0.209059
4            1.163000            1.162208            0.012847            0.000792            0.018260            0.011757
5            1.209000            1.207254            0.019954            0.001746            0.040272            0.026622

sum of residuals :     0.000000

Upper bound for the right tail probability of the largest absolute studentized residual (no. 2) :   1.000000
```
```Control information  -  submodel  1
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

b           omitted

c                          1.873843                 0.306746                 1.397940                 2.255273
a                          1.000000                 0.000000                 1.000000                 1.000000
dep.var.                   1.040800                 0.163655                 0.670000                 1.330000

Number of observations :    5

Multiple correlation coefficient     0.907742    (adjusted   0.905720)
================================

Proportion of variation explained    0.823996    (adjusted   0.820329)
=================================

Standard deviation of the error term              0.069370
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

c                      0.4842988398             0.0323066319               224.720913                 0.000000

a                      0.1332999205             0.0613273100                 4.724458                 0.034701

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

c           a

c           1.000000
a          -0.987122    1.000000

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

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

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

total              50               55.475600

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

mean                1               54.163232             54.163232          11255.564569              0.000000
regression          1                1.081386              1.081386            224.720852              0.000000
residual           48                0.230982              0.004812

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

lack of fit        3                0.015082              0.005027              1.047838              0.380681
pure error        45                0.215900              0.004798

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

reduction          1                0.010070              0.010070              2.142390              0.149935

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

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

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

1            0.790000            0.810321            0.018238           -0.020321           -0.378175           -0.303615
2            0.984000            0.956109            0.011321            0.027891            0.519060            0.407526
3            1.058000            1.054964            0.009856            0.003036            0.056497            0.044211
4            1.163000            1.157080            0.012506            0.005920            0.110169            0.086758
5            1.209000            1.225526            0.015751           -0.016526           -0.307551           -0.244617

sum of residuals :     0.000000

Upper bound for the right tail probability of the largest absolute studentized residual (no. 2) :   1.000000
```
```Control information  -  submodel  2
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

a           omitted
b           omitted

c                          1.873843                 0.306746                 1.397940                 2.255273
dep.var.                   1.040800                 0.163655                 0.670000                 1.330000

Number of observations :    5

There is no constant independent variable in the transformed (sub)model    (message)

Multiple correlation coefficient     0.997711    (adjusted   0.997664)
================================

Proportion of variation explained    0.995427    (adjusted   0.995333)
=================================

Standard deviation of the error term              0.071958
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

c                      0.5536156656             0.0053607978             10664.926934                 0.000000

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

c

c           1.000000

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

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

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

total              50               55.475600

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

regression          1               55.221883             55.221883          10664.926934              0.000000
residual           49                0.253717              0.005178

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

lack of fit        4                0.037817              0.009454              1.970525              0.115263
pure error        45                0.215900              0.004798

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

reduction          2                0.032804              0.016402              3.489644              0.038633

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

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

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

1            0.790000            0.773921            0.007494            0.016079            0.249818            0.224666
2            0.984000            0.940576            0.009108            0.043424            0.674690            0.608353
3            1.058000            1.053580            0.010202            0.004420            0.068669            0.062046
4            1.163000            1.170312            0.011332           -0.007312           -0.113612           -0.102902
5            1.209000            1.248554            0.012090           -0.039554           -0.614569           -0.557614

sum of residuals :     0.170553

Upper bound for the right tail probability of the largest absolute studentized residual (no. 2) :   1.000000

End of job :  1
```
```***********************************
*  Example  2  originates from:   *
*  reference [9],  page 475, ff.  *
***********************************

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

"Input"   18 * [soil sample, available, inorganic, organic];

"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
```
```***********************************
*  Example  3  originates from:   *
*  reference [3],  page 228, 339  *
***********************************

"Model"  Ln (Mean surface volume)  =  Lnalpha  +  beta * Ln (Feed rate)
+  gamma * Ln (Wheel velocity)  +  delta * Ln (Feed viscosity);

"Input"  35 * [Run number, Feed rate, Wheel velocity,
Feed viscosity, Mean surface volume];

"Options" Transformed data matrix, Residual analysis, Process submodels (1);

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

obs.no.      Lnalpha     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

Lnalpha                    1.000000                 0.000000                 1.000000                 1.000000
beta                      -3.454469                 0.748055                -4.439656                -2.263364
gamma                      8.849891                 0.298180                 8.039157                 9.332558
delta                     -1.778466                 0.899585                -2.322788                 0.662688
dep.var.                   3.239746                 0.228501                 2.856470                 3.681351

Number of observations :   35

Multiple correlation coefficient     0.977342    (adjusted   0.975121)
================================

Proportion of variation explained    0.955197    (adjusted   0.950861)
=================================

Standard deviation of the error term              0.050652
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

Lnalpha                8.5495323331             0.2660238985              1032.864643                 0.000000

beta                   0.1684244052             0.0118081196               203.445721                 0.000000

gamma                 -0.5371370141             0.0300960773               318.530024                 0.000000

delta                 -0.0144134670             0.0098170458                 2.155635                 0.152122

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         143182.007167              0.000000
regression          3                1.695702              0.565234            220.306257              0.000000
residual           31                0.079536              0.002566

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

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

1            3.234749            3.293078            0.014784           -0.058329           -1.223587           -1.203971
2            3.453157            3.499877            0.013574           -0.046720           -0.980073           -0.957386
3            3.246491            3.266833            0.014411           -0.020342           -0.426727           -0.418915
4            2.856470            2.845581            0.019237            0.010889            0.228428            0.232392
5            3.642836            3.671117            0.019169           -0.028281           -0.593273           -0.603205
6            2.901422            2.821409            0.020142            0.080013            1.678467            1.721617
7            3.277145            3.185264            0.016296            0.091881            1.927422            1.915802
8            2.960105            3.013233            0.015317           -0.053128           -1.114483           -1.100383
9            3.104587            3.095864            0.015813            0.008723            0.182980            0.181266
10            3.273364            3.319189            0.010115           -0.045825           -0.961298           -0.923297

11            3.250374            3.244114            0.015389            0.006261            0.131334            0.129733
12            3.471966            3.537118            0.016090           -0.065151           -1.366704           -1.356500
13            3.222868            3.246139            0.010877           -0.023271           -0.488175           -0.470406
14            3.681351            3.642772            0.018313            0.038579            0.809285            0.816897
15            3.572346            3.577499            0.027704           -0.005154           -0.108113           -0.121538
16            3.157000            3.136624            0.014274            0.020376            0.427441            0.419268
17            3.095578            3.089933            0.012748            0.005644            0.118401            0.115136
18            3.277145            3.290415            0.015136           -0.013270           -0.278377           -0.274531
19            3.681351            3.551596            0.016891            0.129755            2.721926            2.717208
20            3.449988            3.424209            0.012559            0.025778            0.540765            0.525330

21            3.292126            3.307827            0.013565           -0.015701           -0.329363           -0.321724
22            2.895912            2.938617            0.016603           -0.042705           -0.895839           -0.892395
23            3.346389            3.281716            0.019666            0.064673            1.356676            1.385494
24            3.306887            3.319607            0.010241           -0.012720           -0.266842           -0.256427
25            3.250374            3.267523            0.014593           -0.017148           -0.359731           -0.353541
26            3.139833            3.089357            0.012571            0.050476            1.058853            1.028699
27            3.152736            3.127162            0.016604            0.025574            0.536468            0.534411
28            2.895912            2.917634            0.018272           -0.021722           -0.455674           -0.459805
29            3.430756            3.410283            0.019104            0.020473            0.429475            0.436419
30            3.246491            3.261192            0.017683           -0.014701           -0.308384           -0.309713

31            3.367296            3.392279            0.020625           -0.024983           -0.524074           -0.540015
32            3.091042            3.110356            0.016548           -0.019313           -0.405145           -0.403428
33            2.933857            3.051431            0.013053           -0.117574           -2.466405           -2.402326
34            2.884801            2.862104            0.027070            0.022697            0.476118            0.530148
35            3.346389            3.302140            0.026253            0.044249            0.928227            1.021480

sum of residuals :     0.000000

Upper bound for the right tail probability of the largest absolute studentized residual (no. 19) :   0.161110
```
```Control information  -  submodel  1
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

delta       omitted

Lnalpha                    1.000000                 0.000000                 1.000000                 1.000000
beta                      -3.454469                 0.748055                -4.439656                -2.263364
gamma                      8.849891                 0.298180                 8.039157                 9.332558
dep.var.                   3.239746                 0.228501                 2.856470                 3.681351

Number of observations :   35

Multiple correlation coefficient     0.975747    (adjusted   0.974211)
================================

Proportion of variation explained    0.952082    (adjusted   0.949087)
=================================

Standard deviation of the error term              0.051559
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

Lnalpha                8.6444323107             0.2626702491              1083.056676                 0.000000

beta                   0.1684884827             0.0120193633               196.506767                 0.000000

gamma                 -0.5449387793             0.0301534149               326.604694                 0.000000

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         138191.417269              0.000000
regression          2                1.690171              0.845086            317.901017              0.000000
residual           32                0.085067              0.002658

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

reduction          1                0.005531              0.005531              2.155635              0.152122

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

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

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

1            3.234749            3.288736            0.014744           -0.053986           -1.095063           -1.092714
2            3.453157            3.495338            0.013453           -0.042181           -0.855592           -0.847461
3            3.246491            3.258939            0.013610           -0.012448           -0.252494           -0.250309
4            2.856470            2.835391            0.018263            0.021079            0.427577            0.437186
5            3.642836            3.667170            0.019319           -0.024335           -0.493612           -0.509070
6            2.901422            2.810729            0.019119            0.090693            1.839619            1.894046
7            3.277145            3.179790            0.016148            0.097355            1.974757            1.988259
8            2.960105            3.004546            0.014381           -0.044441           -0.901445           -0.897568
9            3.104587            3.086354            0.014683            0.018233            0.369839            0.368910
10            3.273364            3.312784            0.009289           -0.039420           -0.799600           -0.777283

11            3.250374            3.235443            0.014465            0.014931            0.302866            0.301712
12            3.471966            3.533738            0.016210           -0.061771           -1.252973           -1.262069
13            3.222868            3.238771            0.009822           -0.015903           -0.322584           -0.314204
14            3.681351            3.639046            0.018461            0.042305            0.858113            0.878776
15            3.572346            3.577070            0.028198           -0.004725           -0.095835           -0.109457
16            3.157000            3.127544            0.013095            0.029456            0.597494            0.590683
17            3.095578            3.081275            0.011505            0.014303            0.290113            0.284576
18            3.277145            3.284817            0.014911           -0.007672           -0.155626           -0.155449
19            3.681351            3.545399            0.016648            0.135953            2.757671            2.786075
20            3.449988            3.417901            0.012012            0.032087            0.650846            0.639938

21            3.292126            3.299829            0.012646           -0.007702           -0.156232           -0.154093
22            2.895912            2.928056            0.015231           -0.032144           -0.652013           -0.652569
23            3.346389            3.277298            0.019783            0.069091            1.401447            1.451105
24            3.306887            3.312784            0.009289           -0.005897           -0.119624           -0.116286
25            3.250374            3.258939            0.013610           -0.008564           -0.173721           -0.172218
26            3.139833            3.081275            0.011505            0.058558            1.187784            1.165114
27            3.152736            3.143769            0.012373            0.008967            0.181893            0.179159
28            2.895912            2.933425            0.015036           -0.037513           -0.760916           -0.760637
29            3.430756            3.432323            0.012027           -0.001567           -0.031791           -0.031260
30            3.246491            3.279000            0.013097           -0.032509           -0.659420           -0.651909

31            3.367296            3.410576            0.016728           -0.043280           -0.877901           -0.887443
32            3.091042            3.120529            0.015296           -0.029487           -0.598106           -0.598860
33            2.933857            3.060447            0.011724           -0.126590           -2.567757           -2.521296
34            2.884801            2.893928            0.016507           -0.009128           -0.185143           -0.186866
35            3.346389            3.338135            0.009558            0.008254            0.167433            0.162920

sum of residuals :     0.000000

Upper bound for the right tail probability of the largest absolute studentized residual (no. 19) :   0.125816

End of job :  3
```
```**************************************
*  Example  4  originates from:      *
*  reference [1],  page 88, 93, ff.  *
**************************************

"Model"  y  =  alfa0  +  alfa1 * x;

"Input"  5 * ([x], n, n * [y]);

"Option" Transformed data matrix, Print input data;

"Data"

1.000       4.000       1.100       0.700       1.800       0.400       3.000       5.000       3.000       1.400       4.900
4.400       4.500       5.000       3.000       7.300       8.200       6.200      10.000       4.000      12.000      13.100
12.600      13.200      15.000       4.000      18.700      19.700      17.400      17.100
```
```Transformed data matrix
=======================

obs.no.      alfa0       alfa1       dep.var.     repeats

1          1.000       1.000       1.000       4.000
2          1.000       3.000       3.640       5.000
3          1.000       5.000       7.233       3.000
4          1.000      10.000      12.725       4.000
5          1.000      15.000      18.225       4.000
```
```Control information
===================

transformed variable
denoted by parameter          mean           standard deviation                minimum                  maximum

alfa0                      1.000000                 0.000000                 1.000000                 1.000000
alfa1                      6.700000                 5.262579                 1.000000                15.000000
dep.var.                   8.385000                 6.545571                 0.400000                19.700000

Number of observations :    5

Multiple correlation coefficient     0.987051    (adjusted   0.986326)
================================

Proportion of variation explained    0.974269    (adjusted   0.972840)
=================================

Standard deviation of the error term              1.078736
====================================
```
```Regression parameters
=====================
right  tail
parameter                 estimate           standard deviation              F - ratio              probability

alfa0                  0.1594830832             0.3968072487                 0.161536                 0.692478

alfa1                  1.2276890919             0.0470261690               681.549798                 0.000000

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

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

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

total              20             2220.210000

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

mean                1             1406.164500           1406.164500           1208.387113              0.000000
regression          1              793.099430            793.099430            681.549798              0.000000
residual           18               20.946070              1.163671

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

lack of fit        3                4.252403              1.417468              1.273658              0.319196
pure error        15               16.693667              1.112911

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

regression null hypothesis :  alfa1 = 0

End of job :  4
```
```**************************
*  Marten van Gelderen   *
*  Mathematisch Centrum  *
**************************
```