1 dnl PSPP - a program for statistical analysis.
2 dnl Copyright (C) 2017 Free Software Foundation, Inc.
4 dnl This program is free software: you can redistribute it and/or modify
5 dnl it under the terms of the GNU General Public License as published by
6 dnl the Free Software Foundation, either version 3 of the License, or
7 dnl (at your option) any later version.
9 dnl This program is distributed in the hope that it will be useful,
10 dnl but WITHOUT ANY WARRANTY; without even the implied warranty of
11 dnl MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12 dnl GNU General Public License for more details.
14 dnl You should have received a copy of the GNU General Public License
15 dnl along with this program. If not, see <http://www.gnu.org/licenses/>.
16 dnl AT_BANNER([LINEAR REGRESSION])
18 AT_SETUP([LINEAR REGRESSION - basic])
19 AT_DATA([regression.sps], [dnl
21 data list notable list / v0 to v2.
24 0.65377128 7.735648 -23.97588
25 -0.13087553 6.142625 -19.63854
26 0.34880368 7.651430 -25.26557
27 0.69249021 6.125125 -16.57090
28 -0.07368178 8.245789 -25.80001
29 -0.34404919 6.031540 -17.56743
30 0.75981559 9.832291 -28.35977
31 -0.46958313 5.343832 -16.79548
32 -0.06108490 8.838262 -29.25689
33 0.56154863 6.200189 -18.58219
35 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred resid.
39 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
40 regression.sps:16: warning: REGRESSION: REGRESSION with SAVE ignores FILTER. All cases will be processed.
42 Table: Model Summary (v2)
43 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
47 ,,Sum of Squares,df,Mean Square,F,Sig.
48 ,Regression,202.753,2,101.376,56.754,.000
49 ,Residual,12.504,7,1.786,,
52 Table: Coefficients (v2)
53 ,,Unstandardized Coefficients,,Standardized Coefficients,,
54 ,,B,Std. Error,Beta,t,Sig.
55 ,(Constant),2.191,2.357,.000,.930,.380
56 ,v0,1.813,1.053,.171,1.722,.129
57 ,v1,-3.427,.332,-1.026,-10.334,.000
61 .654,7.736,-23.976,-.84,-23.13
62 -.131,6.143,-19.639,-.54,-19.10
63 .349,7.651,-25.266,-1.87,-23.40
64 .692,6.125,-16.571,.97,-17.54
65 -.074,8.246,-25.800,.40,-26.20
66 -.344,6.032,-17.567,1.53,-19.10
67 .760,9.832,-28.360,1.77,-30.13
68 -.470,5.344,-16.795,.18,-16.97
69 -.061,8.838,-29.257,-1.05,-28.21
70 .562,6.200,-18.582,-.54,-18.04
75 AT_SETUP([LINEAR REGRESSION - one save])
76 AT_DATA([regression.sps], [dnl
78 data list notable list / v0 to v2.
80 0.65377128 7.735648 -23.97588
81 -0.13087553 6.142625 -19.63854
82 0.34880368 7.651430 -25.26557
83 0.69249021 6.125125 -16.57090
84 -0.07368178 8.245789 -25.80001
85 -0.34404919 6.031540 -17.56743
86 0.75981559 9.832291 -28.35977
87 -0.46958313 5.343832 -16.79548
88 -0.06108490 8.838262 -29.25689
89 0.56154863 6.200189 -18.58219
91 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=resid.
92 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred.
96 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
97 Table: Model Summary (v2)
98 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
102 ,,Sum of Squares,df,Mean Square,F,Sig.
103 ,Regression,202.753,2,101.376,56.754,.000
104 ,Residual,12.504,7,1.786,,
107 Table: Coefficients (v2)
108 ,,Unstandardized Coefficients,,Standardized Coefficients,,
109 ,,B,Std. Error,Beta,t,Sig.
110 ,(Constant),2.191,2.357,.000,.930,.380
111 ,v0,1.813,1.053,.171,1.722,.129
112 ,v1,-3.427,.332,-1.026,-10.334,.000
114 Table: Model Summary (v2)
115 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
116 ,.971,.942,.925,1.337
119 ,,Sum of Squares,df,Mean Square,F,Sig.
120 ,Regression,202.753,2,101.376,56.754,.000
121 ,Residual,12.504,7,1.786,,
124 Table: Coefficients (v2)
125 ,,Unstandardized Coefficients,,Standardized Coefficients,,
126 ,,B,Std. Error,Beta,t,Sig.
127 ,(Constant),2.191,2.357,.000,.930,.380
128 ,v0,1.813,1.053,.171,1.722,.129
129 ,v1,-3.427,.332,-1.026,-10.334,.000
133 .654,7.736,-23.976,-.84,-23.13
134 -.131,6.143,-19.639,-.54,-19.10
135 .349,7.651,-25.266,-1.87,-23.40
136 .692,6.125,-16.571,.97,-17.54
137 -.074,8.246,-25.800,.40,-26.20
138 -.344,6.032,-17.567,1.53,-19.10
139 .760,9.832,-28.360,1.77,-30.13
140 -.470,5.344,-16.795,.18,-16.97
141 -.061,8.838,-29.257,-1.05,-28.21
142 .562,6.200,-18.582,-.54,-18.04
147 # Test to ensure that the /SAVE subcommand works properly when SPLIT is active
148 AT_SETUP([LINEAR REGRESSION - SAVE vs SPLITS])
150 # Generate some test data based on a linear model
151 AT_DATA([gen-data.sps], [dnl
155 compute x0 = rv.normal (0,1).
156 compute x1 = rv.normal (0,2).
157 compute err = rv.normal (0,0.1).
158 compute y = 4 - 2 * x0 + 3 * x1 + err.
159 compute g = (#c > 10).
165 print outfile='regdata.txt' /g x0 x1 y err *.
169 AT_CHECK([pspp -O format=csv gen-data.sps], [0], [ignore])
171 # Use our test data to create a predictor and a residual variable
173 AT_DATA([regression0.sps], [dnl
174 data list notable file='regdata.txt' list /g x0 x1 y err *.
185 print outfile='outdata-g0.txt' /g x0 x1 y err res1 pred1 *.
190 AT_CHECK([pspp -O format=csv regression0.sps], [0], [ignore])
192 # Use our test data to create a predictor and a residual variable
194 AT_DATA([regression1.sps], [dnl
195 data list notable file='regdata.txt' list /g x0 x1 y err *.
206 print outfile='outdata-g1.txt' /g x0 x1 y err res1 pred1 *.
211 AT_CHECK([pspp -O format=csv regression1.sps], [0], [ignore])
213 # Use our test data to create a predictor and a residual variable
214 # The data is split on G
215 AT_DATA([regression-split.sps], [dnl
216 data list notable file='regdata.txt' list /g x0 x1 y err *.
227 print outfile='outdata-split.txt' /g x0 x1 y err res1 pred1 *.
231 AT_CHECK([pspp -O format=csv regression-split.sps], [0], [ignore])
233 # The concatenation of G==0 and G==1 should be identical to the SPLIT data
234 AT_CHECK([cat outdata-g0.txt outdata-g1.txt | diff outdata-split.txt - ], [0], [])
239 # Test that the procedure behaves sensibly when presented with
240 # multiple dependent variables
241 AT_SETUP([LINEAR REGRESSION multiple dependent variables])
242 AT_DATA([regression.sps], [dnl
246 compute x0 = rv.normal (0, 1).
247 compute x1 = rv.normal (0, 2).
248 compute err = rv.normal (0, 0.8).
249 compute y = 2 - 1.5 * x0 + 8.4 * x1 + err.
259 /statistics = default.
262 AT_CHECK([pspp -O format=csv regression.sps > output], [0], [ignore])
264 AT_CHECK([head -16 output > first], [0], [])
265 AT_CHECK([tail -16 output > second], [0], [])
267 AT_CHECK([sed -e 's/ycopy/y/g' second | diff first -], [0], [])
272 # Tests the QR decomposition used by the REGRESSION command.
273 AT_SETUP([LINEAR REGRESSION test of QR decomposition])
274 AT_DATA([regression.sps], [dnl
275 data list list / v0 to v1.
277 -12.84099361 0.873270778
278 16.64932538 0.371315664
279 -1.88061907 0.505503722
280 -6.20952354 0.734698282
281 0.33272576 0.891224610
282 -5.54912717 0.052318165
283 6.11832417 0.448853404
284 11.78124974 0.470447593
285 0.75960353 0.565082303
286 6.06432768 0.149316743
287 -2.64919436 0.752532411
288 -10.32250712 0.798263603
289 2.06355038 0.469129797
290 -9.71851742 0.927162270
291 4.65582553 0.250629262
292 9.54574474 0.847032310
293 7.35544368 0.197028541
294 -2.09609740 0.400584261
295 10.30101161 0.671546480
296 -5.24501039 0.929962876
297 1.73412473 0.758161354
298 -3.12732732 0.569785505
299 12.66261501 0.630640223
300 -2.90956805 0.576067804
301 4.89649177 0.624483995
302 13.64613114 0.591089881
303 14.03198397 0.544587572
304 2.23566810 0.967898139
305 5.37367760 0.916246929
306 9.01346888 0.451702743
307 0.75378683 0.235544137
308 -3.47470624 0.742668194
309 -1.02063266 0.860311687
310 -2.67132813 0.082460702
311 23.67661680 0.932553932
312 7.95061359 0.430161125
313 2.05300558 0.066331375
314 -2.01332644 0.163705417
315 20.00663784 0.587292630
316 3.06099417 0.161411889
317 -3.46115358 0.216684625
318 -6.85287183 0.548714855
319 -4.27923809 0.630997663
320 -0.94863395 0.880612945
321 4.47481747 0.359885215
322 -12.80962955 0.886070341
323 9.35753086 0.187176558
324 2.81002235 0.063035095
325 0.01532424 0.964327101
326 0.29867732 0.866408063
327 -2.89035649 0.812135868
328 4.17352811 0.608884061
329 18.15502183 0.920568258
330 -2.92662792 0.550792959
331 -6.08090449 0.965036595
332 -1.09135397 0.862548019
333 7.02816784 0.042277017
334 -21.20245068 0.430673493
335 -8.83397584 0.724976162
336 -0.89055843 0.017934904
337 7.03871587 0.308829557
338 3.84286316 0.685105924
339 4.50280692 0.447635420
340 11.39207346 0.875177896
341 10.86673874 0.518530912
342 7.09853081 0.588367569
343 -12.82864915 0.184667098
344 13.74888760 0.610891139
345 0.37379146 0.557720134
346 -9.79020267 0.942839981
347 0.71574466 0.564570338
348 -17.56040637 0.182061777
349 2.52620466 0.306875011
350 5.37718673 0.366807049
351 -1.83964300 0.465772898
352 6.04848363 0.644501799
353 4.57402403 0.121419591
354 8.55606848 0.373011464
355 -8.46827907 0.491176571
356 -1.77989798 0.734722847
357 -0.68661121 0.540984182
358 1.55798880 0.822587656
359 5.22810831 0.333747878
360 9.50280477 0.068100934
361 -3.74521465 0.248537644
362 1.36045068 0.851827791
363 4.41604088 0.197207162
364 -3.72568327 0.726916693
365 -5.36123334 0.906513529
366 3.61594583 0.414340595
367 -10.01952852 0.140372658
368 25.48681482 0.354309660
369 -3.34529093 0.090075388
370 -18.00437582 0.461438059
371 -5.29782460 0.004362856
372 2.79608522 0.861294398
373 -1.64076209 0.345775481
374 6.82802334 0.137933862
375 -0.45416818 0.404379208
376 -1.66868582 0.797685201
377 -10.02820292 0.075876582
378 5.68232031 0.404815042
379 8.25113850 0.769173748
380 -2.83544237 0.076583474
381 0.87659945 0.092751009
382 6.60270870 0.530444351
383 -12.63924989 0.362099960
384 -6.24451253 0.641993458
385 3.53339015 0.461991892
386 -0.74012232 0.437409755
387 15.37311996 0.974913038
388 -8.09464797 0.543308711
389 -9.61320222 0.221564578
390 0.21843662 0.856512540
391 -1.56958954 0.610709221
392 6.44977372 0.200382138
393 -13.29136274 0.093222309
394 6.46257214 0.024135196
395 -3.82727990 0.601335801
396 0.43081953 0.268230667
397 19.06654416 0.219972815
398 17.02906651 0.996849502
399 -10.18073139 0.012543080
400 12.72088788 0.910600764
401 10.45328185 0.331285901
402 7.14370922 0.896312020
403 -2.81754334 0.048741266
404 6.40217095 0.075796756
405 -3.18030478 0.666325307
406 8.64585957 0.120549153
407 1.37952764 0.899991932
408 -11.81143886 0.601949630
409 0.03899706 0.363808260
410 -10.63828243 0.031092967
411 -6.66940972 0.246204205
412 -5.07374962 0.951272057
413 4.82281566 0.063928187
414 -21.93693564 0.050972680
415 -4.54569883 0.225839693
416 -0.92422779 0.437796785
417 -1.11683029 0.740215139
418 16.77765554 0.851072372
419 9.73614597 0.388180586
420 14.05345168 0.063760129
421 1.20512012 0.665964184
422 8.00307080 0.102447114
423 8.01252623 0.580929209
424 -13.54924183 0.438420739
425 9.87164361 0.970859344
426 17.63437095 0.250501797
427 -3.42503574 0.873290220
428 -2.45873197 0.847756049
429 17.29212092 0.411683187
430 1.15496098 0.530658504
431 -2.14438907 0.592255367
432 -1.79942021 0.517773009
433 -1.30677990 0.830860762
434 1.70233874 0.291826660
435 -3.05532536 0.801767829
436 -4.06732625 0.092294501
437 6.34665476 0.270426235
438 9.46946411 0.196915311
439 14.50919907 0.480357167
440 8.93767237 0.778228613
441 1.90298854 0.903146151
442 18.50500507 0.598561307
443 4.45123027 0.555898218
444 11.37344114 0.616557707
445 -12.14693218 0.409187285
446 18.27198688 0.141619222
447 -5.75939569 0.056989619
448 -4.05515382 0.369281201
449 16.69882098 0.946885257
450 6.39050536 0.679704228
451 4.04213339 0.662792380
452 6.89608366 0.419877433
453 1.56496633 0.358227958
454 5.16679947 0.095144366
455 -3.06280456 0.883265975
456 2.76279175 0.866571973
457 1.84969249 0.264869828
458 21.79840498 0.702650979
459 1.42450528 0.719308635
460 0.96797046 0.111937435
461 18.26840323 0.075621738
462 13.38288377 0.573399086
463 2.41101500 0.766238677
464 3.83866337 0.499888953
465 -1.56577367 0.695244089
466 -0.90342790 0.671654151
467 10.83775583 0.026041124
468 -9.89767935 0.745297991
469 11.74840150 0.309144074
470 1.73069359 0.814063985
471 -5.27966183 0.591005828
472 3.33030043 0.559401806
473 1.31427975 0.520950237
474 -10.04588558 0.507008362
475 10.41228345 0.425867272
476 1.71961097 0.595783108
477 -17.54904427 0.328788939
478 -2.23545419 0.223377350
479 -8.68774333 0.980964240
480 -3.48048220 0.008877675
481 -3.69635326 0.090236718
482 9.76114237 0.769375983
483 -10.25662038 0.508137553
484 0.11155446 0.468504431
485 -8.06824580 0.414098962
486 3.10031660 0.327130207
487 -3.33393146 0.756896774
488 -3.96276749 0.530956360
489 14.53610268 0.846474699
490 1.70505918 0.754662464
491 -1.93495001 0.656650411
492 5.01974522 0.745337633
493 13.41249973 0.489362476
494 11.49288744 0.335924476
495 12.59019763 0.155560469
496 -10.17947298 0.677318449
497 0.05556115 0.655090105
498 3.82092860 0.051838719
499 8.23041456 0.918272190
500 -0.50314649 0.772015826
501 20.05162157 0.880265258
502 8.98816884 0.666646668
503 -6.28312120 0.138534416
504 3.68589909 0.274559458
505 0.59699510 0.253180863
506 -2.74783135 0.983525221
507 0.32515065 0.839969577
508 -3.60606166 0.330646732
509 -0.82037740 0.129591173
510 6.12444860 0.098536516
511 10.95671074 0.033546728
512 -2.84911174 0.720288722
513 6.04597572 0.577061422
514 -0.60147150 0.674096868
515 -5.30458364 0.291468008
516 2.68044943 0.379853840
517 0.85986585 0.984214339
518 -12.77906359 0.882390290
519 7.21420144 0.550884826
520 2.31817022 0.231021556
521 11.60161950 0.888496654
522 -0.19346228 0.242609713
523 5.07478120 0.759161318
524 14.54155003 0.040387654
525 3.81039636 0.874572741
526 2.23233049 0.448317248
527 0.19481869 0.201906051
528 2.81530451 0.132131690
529 12.39893259 0.674693704
530 0.47054642 0.632959494
531 2.16152913 0.734480632
532 0.33398836 0.315024718
533 7.35509037 0.304570986
534 -2.92336559 0.539062343
535 5.79622573 0.392393310
536 -2.37607425 0.403380474
537 0.04498550 0.756875541
538 -1.63674414 0.613789514
539 11.80310547 0.832651469
540 6.30630243 0.850689403
541 1.48394652 0.096243229
542 4.03361865 0.799660045
543 3.54707273 0.408520520
544 2.00327040 0.702944912
545 17.30761707 0.380542812
546 5.72738968 0.105447516
547 -13.64604891 0.328506659
548 8.35976334 0.702173924
549 -7.41197443 0.134396488
550 -15.95683040 0.618526462
551 8.76889573 0.950243069
552 -1.13482624 0.113477080
553 -0.60311407 0.090444247
554 4.95508365 0.612511543
555 5.36934491 0.979213258
556 -0.03554882 0.807185690
557 -11.58131144 0.183341373
558 4.46809041 0.796330582
559 12.49741067 0.346860912
560 8.63824488 0.073684997
561 0.49990913 0.732519306
562 12.82688360 0.109400213
563 13.20375065 0.850369092
564 -8.41110869 0.177717087
565 16.31959963 0.727704840
566 17.59203613 0.235311681
567 0.32148420 0.842195936
568 5.43148331 0.670904647
569 7.14649727 0.028190029
570 0.25410683 0.421535783
571 -12.41047826 0.086404379
572 -10.64180909 0.229659236
573 -6.40185653 0.876365242
574 15.63063324 0.667672536
575 1.94280423 0.799266628
576 -5.76507450 0.367344192
577 8.60895533 0.154109357
578 9.38306751 0.788742770
579 3.43573528 0.284535277
580 4.81848966 0.872283177
581 11.65839314 0.234109111
582 -5.57884822 0.030363060
583 -3.94238060 0.325320686
584 9.38133340 0.201141788
585 -7.65003459 0.647734396
586 11.23091019 0.084927159
587 -6.07705432 0.037273791
588 7.46380750 0.506897136
589 7.42034855 0.869351148
590 -4.43031973 0.231191152
591 -1.07351537 0.480234836
592 -1.40653281 0.690620421
593 -3.82710168 0.990191328
594 5.04583490 0.543427375
595 -11.54265099 0.270542185
596 0.49059479 0.991447248
597 -1.40871469 0.555998766
598 3.64241437 0.743840673
599 -18.30031589 0.357478210
600 4.27487959 0.770619738
601 1.28805821 0.654787106
602 -3.19542768 0.218110139
603 12.53375654 0.011857644
604 11.78889419 0.054127726
605 -5.38392310 0.839309080
606 16.38024181 0.228801038
607 -0.59622631 0.134381782
608 -0.74107258 0.258146632
609 -12.31429450 0.020524447
610 -0.79785028 0.968028764
611 6.39899711 0.038162566
612 7.42024044 0.716163692
613 -3.62470664 0.018201813
614 -2.55049724 0.162446610
615 -10.79888854 0.683070478
616 10.18490144 0.546461234
617 -2.76979044 0.198830067
618 4.85164813 0.094100357
619 0.96477200 0.381801756
620 8.13344336 0.639730450
621 9.04684412 0.786084368
622 10.41746272 0.828304181
623 0.94334368 0.798419831
624 10.13116556 0.191715972
625 -4.12728628 0.575178239
626 -9.59222379 0.876405375
627 1.64680258 0.391003085
628 -4.58897613 0.039176486
629 0.38394379 0.511577564
630 -4.80428215 0.222785463
631 0.35363661 0.681658725
632 -9.63685708 0.183035382
633 3.54363414 0.766127414
634 6.89610808 0.967514568
635 -2.03781105 0.464416752
636 8.67956196 0.421424078
637 -1.09959038 0.061231448
638 7.12587456 0.028601318
639 -6.93064672 0.402561175
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1692 6.10056565 0.418383130
1693 10.48099521 0.333593221
1694 19.28363092 0.382408442
1695 2.12080726 0.601206970
1696 -6.82450704 0.740158518
1697 11.32395692 0.627015570
1698 5.00040701 0.476274658
1699 -11.64750733 0.105099095
1700 5.77442654 0.576560214
1701 0.31340364 0.516479036
1702 -2.09881449 0.146089191
1703 5.12411327 0.368130477
1704 1.70530391 0.621828438
1705 -12.95649749 0.355726301
1706 8.43735652 0.275383759
1707 -15.56161079 0.413160084
1708 5.28942694 0.069125495
1709 5.96040877 0.438716686
1710 -2.59318107 0.571116303
1711 6.95988992 0.650760909
1712 14.00074797 0.623645969
1713 1.66101456 0.558763985
1714 -2.57968349 0.648185379
1715 -5.47584253 0.716901151
1716 6.37222581 0.060563130
1717 2.83664864 0.842419730
1718 1.48926558 0.620280308
1719 0.33471689 0.170312461
1720 5.21648412 0.317639631
1721 0.51733642 0.843867329
1722 9.86005834 0.306036746
1723 -5.81145791 0.975655452
1724 -5.43219061 0.303385368
1725 5.87157118 0.677369776
1726 2.08889926 0.310200439
1727 -2.53433085 0.194730908
1728 7.01359575 0.674259533
1729 -2.00936260 0.682056466
1730 -2.98240739 0.787899917
1731 -7.43289210 0.357483044
1732 -12.58905988 0.981387385
1733 5.78095517 0.533526274
1734 -1.23065889 0.687266774
1735 -6.82309960 0.293249774
1736 8.47000829 0.842056399
1737 -5.81624772 0.303700280
1738 -14.83571031 0.311387926
1739 4.66808472 0.091222946
1740 -2.90144463 0.438301785
1741 10.62458662 0.828335698
1742 7.88002491 0.990156110
1743 10.27680283 0.251087079
1744 -9.42498970 0.292462244
1745 6.73027640 0.213065205
1746 1.28169895 0.353152789
1747 -14.29203733 0.264563048
1748 20.35772711 0.265208837
1749 3.55095071 0.242905653
1750 -17.97067670 0.373951756
1751 10.53141139 0.247520698
1752 0.05293205 0.579940423
1753 12.79674707 0.288031751
1754 -5.44235185 0.075899079
1755 14.29464811 0.960707538
1756 -1.36753291 0.124265178
1757 -4.25946974 0.521720352
1758 -12.46519252 0.385503339
1759 -6.65343143 0.540942219
1760 5.55949184 0.143194404
1761 -1.20480594 0.515905644
1762 -4.13839908 0.164461445
1763 -2.21345425 0.812969725
1764 3.94223380 0.229238952
1765 -10.78661097 0.395049514
1766 3.06997341 0.791234255
1767 24.82205477 0.110859039
1768 6.28791249 0.867125744
1769 -2.80296119 0.703583849
1770 13.24274039 0.425951975
1771 -0.19577471 0.361568727
1772 -2.34894781 0.954814545
1773 19.76339577 0.635462177
1774 -1.87591480 0.149121567
1775 -7.70962391 0.711708342
1776 -2.46291902 0.390902746
1778 regression /variables=v0 v1 /statistics defaults /dependent=v0 /method=enter.
1781 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
1782 Table: Reading free-form data from INLINE.
1787 Table: Model Summary (v0)
1788 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
1792 ,,Sum of Squares,df,Mean Square,F,Sig.
1793 ,Regression,235.23,1,235.23,3.58,.059
1794 ,Residual,98438.40,1498,65.71,,
1795 ,Total,98673.63,1499,,,
1797 Table: Coefficients (v0)
1798 ,,Unstandardized Coefficients,,Standardized Coefficients,,
1799 ,,B,Std. Error,Beta,t,Sig.
1800 ,(Constant),1.24,.42,.00,2.95,.003
1801 ,v1,1.37,.72,.05,1.89,.059
1806 AT_SETUP([LINEAR REGRESSION no crash on all missing])
1807 AT_DATA([regcrash.sps], [dnl
1808 data list list /x * y.
1823 regression /variables=x y /dependent=y.
1826 AT_CHECK([pspp -o pspp.csv regcrash.sps], [1], [ignore], [ignore])
1832 AT_SETUP([LINEAR REGRESSION missing dependent variable])
1834 dnl Test for a bug where missing values in the dependent variable were not being
1835 dnl ignored like they should have been.
1836 AT_DATA([reg-mdv-ref.sps], [dnl
1837 data list notable list / v0 to v2.
1839 0.65377128 7.735648 -23.97588
1840 -0.13087553 6.142625 -19.63854
1841 0.34880368 7.651430 -25.26557
1842 0.69249021 6.125125 -16.57090
1843 -0.07368178 8.245789 -25.80001
1844 -0.34404919 6.031540 -17.56743
1845 0.75981559 9.832291 -28.35977
1846 -0.46958313 5.343832 -16.79548
1847 -0.06108490 8.838262 -29.25689
1848 0.56154863 6.200189 -18.58219
1850 regression /variables=v0 v1
1851 /statistics defaults
1856 AT_CHECK([pspp -o pspp-ref.csv reg-mdv-ref.sps])
1858 AT_DATA([reg-mdv.sps], [dnl
1859 data list notable list / v0 to v2.
1861 0.65377128 7.735648 -23.97588
1862 -0.13087553 6.142625 -19.63854
1863 0.34880368 7.651430 -25.26557
1864 0.69249021 6.125125 -16.57090
1865 -0.07368178 8.245789 -25.80001
1866 -0.34404919 6.031540 -17.56743
1867 0.75981559 9.832291 -28.35977
1868 -0.46958313 5.343832 -16.79548
1869 -0.06108490 8.838262 -29.25689
1870 0.56154863 6.200189 -18.58219
1874 missing values v2 (9).
1876 regression /variables=v0 v1
1877 /statistics defaults
1882 AT_CHECK([pspp -o pspp.csv reg-mdv.sps])
1884 AT_CHECK([diff pspp.csv pspp-ref.csv])
1889 AT_SETUP([LINEAR REGRESSION with invalid syntax (and empty dataset)])
1891 AT_DATA([ss.sps], [dnl
1892 data list notable list / v0 to v2.
1896 regression /variables=v0 v1
1897 /statistics r coeff anova
1902 AT_CHECK([pspp ss.sps], [1], [ignore])
1907 dnl The following example comes from
1908 dnl http://www.ats.ucla.edu/stat/spss/output/reg_spss%28long%29.htm
1909 AT_SETUP([LINEAR REGRESSION coefficient confidence interval])
1911 AT_DATA([conf.sps], [dnl
1914 data list notable list /math female socst read science *
1916 41.00 .00 57.00 57.00 47.00
1917 53.00 1.00 61.00 68.00 63.00
1918 54.00 .00 31.00 44.00 58.00
1919 47.00 .00 56.00 63.00 53.00
1920 57.00 .00 61.00 47.00 53.00
1921 51.00 .00 61.00 44.00 63.00
1922 42.00 .00 61.00 50.00 53.00
1923 45.00 .00 36.00 34.00 39.00
1924 54.00 .00 51.00 63.00 58.00
1925 52.00 .00 51.00 57.00 50.00
1926 51.00 .00 61.00 60.00 53.00
1927 51.00 .00 61.00 57.00 63.00
1928 71.00 .00 71.00 73.00 61.00
1929 57.00 .00 46.00 54.00 55.00
1930 50.00 .00 56.00 45.00 31.00
1931 43.00 .00 56.00 42.00 50.00
1932 51.00 .00 56.00 47.00 50.00
1933 60.00 .00 56.00 57.00 58.00
1934 62.00 .00 61.00 68.00 55.00
1935 57.00 .00 46.00 55.00 53.00
1936 35.00 .00 41.00 63.00 66.00
1937 75.00 .00 66.00 63.00 72.00
1938 45.00 .00 56.00 50.00 55.00
1939 57.00 .00 61.00 60.00 61.00
1940 45.00 .00 46.00 37.00 39.00
1941 46.00 .00 31.00 34.00 39.00
1942 66.00 .00 66.00 65.00 61.00
1943 57.00 .00 46.00 47.00 58.00
1944 49.00 .00 46.00 44.00 39.00
1945 49.00 .00 41.00 52.00 55.00
1946 57.00 .00 51.00 42.00 47.00
1947 64.00 .00 61.00 76.00 64.00
1948 63.00 .00 71.00 65.00 66.00
1949 57.00 .00 31.00 42.00 72.00
1950 50.00 .00 61.00 52.00 61.00
1951 58.00 .00 66.00 60.00 61.00
1952 75.00 .00 66.00 68.00 66.00
1953 68.00 .00 66.00 65.00 66.00
1954 44.00 .00 36.00 47.00 36.00
1955 40.00 .00 51.00 39.00 39.00
1956 41.00 .00 51.00 47.00 42.00
1957 62.00 .00 51.00 55.00 58.00
1958 57.00 .00 51.00 52.00 55.00
1959 43.00 .00 41.00 42.00 50.00
1960 48.00 .00 66.00 65.00 63.00
1961 63.00 .00 46.00 55.00 69.00
1962 39.00 .00 47.00 50.00 49.00
1963 70.00 .00 51.00 65.00 63.00
1964 63.00 .00 46.00 47.00 53.00
1965 59.00 .00 51.00 57.00 47.00
1966 61.00 .00 56.00 53.00 57.00
1967 38.00 .00 41.00 39.00 47.00
1968 61.00 .00 46.00 44.00 50.00
1969 49.00 .00 71.00 63.00 55.00
1970 73.00 .00 66.00 73.00 69.00
1971 44.00 .00 42.00 39.00 26.00
1972 42.00 .00 32.00 37.00 33.00
1973 39.00 .00 46.00 42.00 56.00
1974 55.00 .00 41.00 63.00 58.00
1975 52.00 .00 51.00 48.00 44.00
1976 45.00 .00 61.00 50.00 58.00
1977 61.00 .00 66.00 47.00 69.00
1978 39.00 .00 46.00 44.00 34.00
1979 41.00 .00 36.00 34.00 36.00
1980 50.00 .00 61.00 50.00 36.00
1981 40.00 .00 26.00 44.00 50.00
1982 60.00 .00 66.00 60.00 55.00
1983 47.00 .00 26.00 47.00 42.00
1984 59.00 .00 44.00 63.00 65.00
1985 49.00 .00 36.00 50.00 44.00
1986 46.00 .00 51.00 44.00 39.00
1987 58.00 .00 61.00 60.00 58.00
1988 71.00 .00 66.00 73.00 63.00
1989 58.00 .00 66.00 68.00 74.00
1990 46.00 .00 51.00 55.00 58.00
1991 43.00 .00 31.00 47.00 45.00
1992 54.00 .00 61.00 55.00 49.00
1993 56.00 .00 66.00 68.00 63.00
1994 46.00 .00 46.00 31.00 39.00
1995 54.00 .00 56.00 47.00 42.00
1996 57.00 .00 56.00 63.00 55.00
1997 54.00 .00 36.00 36.00 61.00
1998 71.00 .00 56.00 68.00 66.00
1999 48.00 .00 56.00 63.00 63.00
2000 40.00 .00 41.00 55.00 44.00
2001 64.00 .00 66.00 55.00 63.00
2002 51.00 .00 56.00 52.00 53.00
2003 39.00 .00 56.00 34.00 42.00
2004 40.00 .00 31.00 50.00 34.00
2005 61.00 .00 56.00 55.00 61.00
2006 66.00 .00 46.00 52.00 47.00
2007 49.00 .00 46.00 63.00 66.00
2008 65.00 1.00 61.00 68.00 69.00
2009 52.00 1.00 48.00 39.00 44.00
2010 46.00 1.00 51.00 44.00 47.00
2011 61.00 1.00 51.00 50.00 63.00
2012 72.00 1.00 56.00 71.00 66.00
2013 71.00 1.00 71.00 63.00 69.00
2014 40.00 1.00 41.00 34.00 39.00
2015 69.00 1.00 61.00 63.00 61.00
2016 64.00 1.00 66.00 68.00 69.00
2017 56.00 1.00 61.00 47.00 66.00
2018 49.00 1.00 41.00 47.00 33.00
2019 54.00 1.00 51.00 63.00 50.00
2020 53.00 1.00 51.00 52.00 61.00
2021 66.00 1.00 56.00 55.00 42.00
2022 67.00 1.00 56.00 60.00 50.00
2023 40.00 1.00 33.00 35.00 51.00
2024 46.00 1.00 56.00 47.00 50.00
2025 69.00 1.00 71.00 71.00 58.00
2026 40.00 1.00 56.00 57.00 61.00
2027 41.00 1.00 51.00 44.00 39.00
2028 57.00 1.00 66.00 65.00 46.00
2029 58.00 1.00 56.00 68.00 59.00
2030 57.00 1.00 66.00 73.00 55.00
2031 37.00 1.00 41.00 36.00 42.00
2032 55.00 1.00 46.00 43.00 55.00
2033 62.00 1.00 66.00 73.00 58.00
2034 64.00 1.00 56.00 52.00 58.00
2035 40.00 1.00 51.00 41.00 39.00
2036 50.00 1.00 51.00 60.00 50.00
2037 46.00 1.00 56.00 50.00 50.00
2038 53.00 1.00 56.00 50.00 39.00
2039 52.00 1.00 46.00 47.00 48.00
2040 45.00 1.00 46.00 47.00 34.00
2041 56.00 1.00 61.00 55.00 58.00
2042 45.00 1.00 56.00 50.00 44.00
2043 54.00 1.00 41.00 39.00 50.00
2044 56.00 1.00 46.00 50.00 47.00
2045 41.00 1.00 26.00 34.00 29.00
2046 54.00 1.00 56.00 57.00 50.00
2047 72.00 1.00 56.00 57.00 54.00
2048 56.00 1.00 51.00 68.00 50.00
2049 47.00 1.00 46.00 42.00 47.00
2050 49.00 1.00 66.00 61.00 44.00
2051 60.00 1.00 66.00 76.00 67.00
2052 54.00 1.00 46.00 47.00 58.00
2053 55.00 1.00 56.00 46.00 44.00
2054 33.00 1.00 41.00 39.00 42.00
2055 49.00 1.00 61.00 52.00 44.00
2056 43.00 1.00 51.00 28.00 44.00
2057 50.00 1.00 52.00 42.00 50.00
2058 52.00 1.00 51.00 47.00 39.00
2059 48.00 1.00 41.00 47.00 44.00
2060 58.00 1.00 66.00 52.00 53.00
2061 43.00 1.00 61.00 47.00 48.00
2062 41.00 1.00 31.00 50.00 55.00
2063 43.00 1.00 51.00 44.00 44.00
2064 46.00 1.00 41.00 47.00 40.00
2065 44.00 1.00 41.00 45.00 34.00
2066 43.00 1.00 46.00 47.00 42.00
2067 61.00 1.00 56.00 65.00 58.00
2068 40.00 1.00 51.00 43.00 50.00
2069 49.00 1.00 61.00 47.00 53.00
2070 56.00 1.00 66.00 57.00 58.00
2071 61.00 1.00 71.00 68.00 55.00
2072 50.00 1.00 61.00 52.00 54.00
2073 51.00 1.00 61.00 42.00 47.00
2074 42.00 1.00 41.00 42.00 42.00
2075 67.00 1.00 66.00 66.00 61.00
2076 53.00 1.00 61.00 47.00 53.00
2077 50.00 1.00 58.00 57.00 51.00
2078 51.00 1.00 31.00 47.00 63.00
2079 72.00 1.00 61.00 57.00 61.00
2080 48.00 1.00 61.00 52.00 55.00
2081 40.00 1.00 31.00 44.00 40.00
2082 53.00 1.00 61.00 50.00 61.00
2083 39.00 1.00 36.00 39.00 47.00
2084 63.00 1.00 41.00 57.00 55.00
2085 51.00 1.00 37.00 57.00 53.00
2086 45.00 1.00 43.00 42.00 50.00
2087 39.00 1.00 61.00 47.00 47.00
2088 42.00 1.00 39.00 42.00 31.00
2089 62.00 1.00 51.00 60.00 61.00
2090 44.00 1.00 51.00 44.00 35.00
2091 65.00 1.00 66.00 63.00 54.00
2092 63.00 1.00 71.00 65.00 55.00
2093 54.00 1.00 41.00 39.00 53.00
2094 45.00 1.00 36.00 50.00 58.00
2095 60.00 1.00 51.00 52.00 56.00
2096 49.00 1.00 51.00 60.00 50.00
2097 48.00 1.00 51.00 44.00 39.00
2098 57.00 1.00 61.00 52.00 63.00
2099 55.00 1.00 61.00 55.00 50.00
2100 66.00 1.00 56.00 50.00 66.00
2101 64.00 1.00 71.00 65.00 58.00
2102 55.00 1.00 51.00 52.00 53.00
2103 42.00 1.00 36.00 47.00 42.00
2104 56.00 1.00 61.00 63.00 55.00
2105 53.00 1.00 66.00 50.00 53.00
2106 41.00 1.00 41.00 42.00 42.00
2107 42.00 1.00 41.00 36.00 50.00
2108 53.00 1.00 56.00 50.00 55.00
2109 42.00 1.00 51.00 41.00 34.00
2110 60.00 1.00 56.00 47.00 50.00
2111 52.00 1.00 56.00 55.00 42.00
2112 38.00 1.00 46.00 42.00 36.00
2113 57.00 1.00 52.00 57.00 55.00
2114 58.00 1.00 61.00 55.00 58.00
2115 65.00 1.00 61.00 63.00 53.00
2119 /variables = math female socst read
2120 /statistics = coeff r anova ci (95)
2121 /dependent = science
2125 AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
2126 Table: Model Summary (science)
2127 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2128 ,.699,.489,.479,7.148
2130 Table: ANOVA (science)
2131 ,,Sum of Squares,df,Mean Square,F,Sig.
2132 ,Regression,9543.721,4,2385.930,46.695,.000
2133 ,Residual,9963.779,195,51.096,,
2134 ,Total,19507.500,199,,,
2136 Table: Coefficients (science)
2137 ,,Unstandardized Coefficients,,Standardized Coefficients,,,95% Confidence Interval for B,
2138 ,,B,Std. Error,Beta,t,Sig.,Lower Bound,Upper Bound
2139 ,(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
2140 ,math,.389,.074,.368,5.252,.000,.243,.535
2141 ,female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
2142 ,socst,.050,.062,.054,.801,.424,-.073,.173
2143 ,read,.335,.073,.347,4.607,.000,.192,.479
2150 dnl Checks for regression against bug #44877.
2151 AT_SETUP([LINEAR REGRESSION crash with long string variables])
2152 AT_DATA([regression.sps], [dnl
2155 DATA LIST notable LIST /text (A24) Y * X1 *
2157 V00276601 0.00 90.00
2158 V00292909 10.00 30.00
2159 V00291204 20.00 20.00
2160 V00300070 0.00 90.00
2167 /STATISTICS=COEFF R ANOVA
2172 AT_CHECK([pspp -o pspp.csv regression.sps])
2173 AT_CHECK([cat pspp.csv], [0], [dnl
2174 Table: Model Summary (X1)
2175 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2179 ,,Sum of Squares,df,Mean Square,F,Sig.
2180 ,Regression,3820.45,1,3820.45,16.81,.055
2181 ,Residual,454.55,2,227.27,,
2184 Table: Coefficients (X1)
2185 ,,Unstandardized Coefficients,,Standardized Coefficients,,
2186 ,,B,Std. Error,Beta,t,Sig.
2187 ,(Constant),85.45,10.16,.00,8.41,.004
2188 ,Y,-3.73,.91,-.95,-4.10,.055
2192 V00276601 ,.00,90.00,4.55
2193 V00292909 ,10.00,30.00,-18.18
2194 V00291204 ,20.00,20.00,9.09
2195 V00300070 ,.00,90.00,4.55
2200 dnl Test for a crash which happened on bad input syntax
2201 AT_SETUP([LINEAR REGRESSION -- Empty Parentheses])
2203 AT_DATA([empty-parens.sps], [dnl
2206 data list notable list /math female socst read science *
2208 58.00 1.00 61.00 55.00 58.00
2209 65.00 1.00 61.00 63.00 53.00
2213 /variables = math female socst read
2214 /statistics = coeff r anova ci ()
2215 /dependent = science
2219 AT_CHECK([pspp -o pspp.csv empty-parens.sps], [1], [ignore])
2226 AT_SETUP([LINEAR REGRESSION varibles on ENTER subcommand])
2227 AT_DATA([regression.sps], [dnl
2230 DATA LIST notable LIST /number * value *.
2254 /STATISTICS COEFF R ANOVA
2256 /METHOD=ENTER number.
2260 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
2261 Table: Model Summary (value)
2262 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2263 ,.612,.374,.338,6.176
2265 Table: ANOVA (value)
2266 ,,Sum of Squares,df,Mean Square,F,Sig.
2267 ,Regression,388.065,1,388.065,10.173,.005
2268 ,Residual,648.498,17,38.147,,
2269 ,Total,1036.563,18,,,
2271 Table: Coefficients (value)
2272 ,,Unstandardized Coefficients,,Standardized Coefficients,,
2273 ,,B,Std. Error,Beta,t,Sig.
2274 ,(Constant),.927,2.247,.000,.413,.685
2275 ,number,.611,.192,.612,3.189,.005
2282 AT_SETUP([LINEAR REGRESSION /ORIGIN])
2283 AT_DATA([regression-origin.sps], [dnl
2286 DATA LIST notable LIST /number * value *.
2310 /STATISTICS COEFF R ANOVA
2313 /METHOD=ENTER number.
2317 AT_CHECK([pspp -O format=csv regression-origin.sps], [0], [dnl
2318 Table: Model Summary (value)
2319 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2320 ,.802,.643,.622,6.032
2322 Table: ANOVA (value)
2323 ,,Sum of Squares,df,Mean Square,F,Sig.
2324 ,Regression,1181.726,1,1181.726,32.475,.000
2325 ,Residual,654.989,18,36.388,,
2326 ,Total,1836.715,19,,,
2328 Table: Coefficients (value)
2329 ,,Unstandardized Coefficients,,Standardized Coefficients,,
2330 ,,B,Std. Error,Beta,t,Sig.
2331 ,number,.672,.118,.802,5.699,.000