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/>.
17 AT_BANNER([LINEAR REGRESSION])
19 AT_SETUP([LINEAR REGRESSION - basic])
20 AT_DATA([regression.sps], [dnl
22 data list notable list / v0 to v2.
25 0.65377128 7.735648 -23.97588
26 -0.13087553 6.142625 -19.63854
27 0.34880368 7.651430 -25.26557
28 0.69249021 6.125125 -16.57090
29 -0.07368178 8.245789 -25.80001
30 -0.34404919 6.031540 -17.56743
31 0.75981559 9.832291 -28.35977
32 -0.46958313 5.343832 -16.79548
33 -0.06108490 8.838262 -29.25689
34 0.56154863 6.200189 -18.58219
36 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred resid.
40 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
41 regression.sps:16: warning: REGRESSION: REGRESSION with SAVE ignores FILTER. All cases will be processed.
43 Table: Model Summary (v2)
44 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
48 ,,Sum of Squares,df,Mean Square,F,Sig.
49 ,Regression,202.753,2,101.376,56.754,.000
50 ,Residual,12.504,7,1.786,,
53 Table: Coefficients (v2)
54 ,,Unstandardized Coefficients,,Standardized Coefficients,,
55 ,,B,Std. Error,Beta,t,Sig.
56 ,(Constant),2.191,2.357,.000,.930,.380
57 ,v0,1.813,1.053,.171,1.722,.129
58 ,v1,-3.427,.332,-1.026,-10.334,.000
62 .654,7.736,-23.976,-.84,-23.13
63 -.131,6.143,-19.639,-.54,-19.10
64 .349,7.651,-25.266,-1.87,-23.40
65 .692,6.125,-16.571,.97,-17.54
66 -.074,8.246,-25.800,.40,-26.20
67 -.344,6.032,-17.567,1.53,-19.10
68 .760,9.832,-28.360,1.77,-30.13
69 -.470,5.344,-16.795,.18,-16.97
70 -.061,8.838,-29.257,-1.05,-28.21
71 .562,6.200,-18.582,-.54,-18.04
76 AT_SETUP([LINEAR REGRESSION - one save])
77 AT_DATA([regression.sps], [dnl
79 data list notable list / v0 to v2.
81 0.65377128 7.735648 -23.97588
82 -0.13087553 6.142625 -19.63854
83 0.34880368 7.651430 -25.26557
84 0.69249021 6.125125 -16.57090
85 -0.07368178 8.245789 -25.80001
86 -0.34404919 6.031540 -17.56743
87 0.75981559 9.832291 -28.35977
88 -0.46958313 5.343832 -16.79548
89 -0.06108490 8.838262 -29.25689
90 0.56154863 6.200189 -18.58219
92 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=resid.
93 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred.
97 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
98 Table: Model Summary (v2)
99 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
100 ,.971,.942,.925,1.337
103 ,,Sum of Squares,df,Mean Square,F,Sig.
104 ,Regression,202.753,2,101.376,56.754,.000
105 ,Residual,12.504,7,1.786,,
108 Table: Coefficients (v2)
109 ,,Unstandardized Coefficients,,Standardized Coefficients,,
110 ,,B,Std. Error,Beta,t,Sig.
111 ,(Constant),2.191,2.357,.000,.930,.380
112 ,v0,1.813,1.053,.171,1.722,.129
113 ,v1,-3.427,.332,-1.026,-10.334,.000
115 Table: Model Summary (v2)
116 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
117 ,.971,.942,.925,1.337
120 ,,Sum of Squares,df,Mean Square,F,Sig.
121 ,Regression,202.753,2,101.376,56.754,.000
122 ,Residual,12.504,7,1.786,,
125 Table: Coefficients (v2)
126 ,,Unstandardized Coefficients,,Standardized Coefficients,,
127 ,,B,Std. Error,Beta,t,Sig.
128 ,(Constant),2.191,2.357,.000,.930,.380
129 ,v0,1.813,1.053,.171,1.722,.129
130 ,v1,-3.427,.332,-1.026,-10.334,.000
134 .654,7.736,-23.976,-.84,-23.13
135 -.131,6.143,-19.639,-.54,-19.10
136 .349,7.651,-25.266,-1.87,-23.40
137 .692,6.125,-16.571,.97,-17.54
138 -.074,8.246,-25.800,.40,-26.20
139 -.344,6.032,-17.567,1.53,-19.10
140 .760,9.832,-28.360,1.77,-30.13
141 -.470,5.344,-16.795,.18,-16.97
142 -.061,8.838,-29.257,-1.05,-28.21
143 .562,6.200,-18.582,-.54,-18.04
148 # Test to ensure that the /SAVE subcommand works properly when SPLIT is active
149 AT_SETUP([LINEAR REGRESSION - SAVE vs SPLITS])
151 # Generate some test data based on a linear model
152 AT_DATA([gen-data.sps], [dnl
156 compute x0 = rv.normal (0,1).
157 compute x1 = rv.normal (0,2).
158 compute err = rv.normal (0,0.1).
159 compute y = 4 - 2 * x0 + 3 * x1 + err.
160 compute g = (#c > 10).
166 print outfile='regdata.txt' /g x0 x1 y err *.
170 AT_CHECK([pspp -O format=csv gen-data.sps], [0], [ignore])
172 # Use our test data to create a predictor and a residual variable
174 AT_DATA([regression0.sps], [dnl
175 data list notable file='regdata.txt' list /g x0 x1 y err *.
186 print outfile='outdata-g0.txt' /g x0 x1 y err res1 pred1 *.
191 AT_CHECK([pspp -O format=csv regression0.sps], [0], [ignore])
193 # Use our test data to create a predictor and a residual variable
195 AT_DATA([regression1.sps], [dnl
196 data list notable file='regdata.txt' list /g x0 x1 y err *.
207 print outfile='outdata-g1.txt' /g x0 x1 y err res1 pred1 *.
212 AT_CHECK([pspp -O format=csv regression1.sps], [0], [ignore])
214 # Use our test data to create a predictor and a residual variable
215 # The data is split on G
216 AT_DATA([regression-split.sps], [dnl
217 data list notable file='regdata.txt' list /g x0 x1 y err *.
228 print outfile='outdata-split.txt' /g x0 x1 y err res1 pred1 *.
232 AT_CHECK([pspp -O format=csv regression-split.sps], [0], [ignore])
234 # The concatenation of G==0 and G==1 should be identical to the SPLIT data
235 AT_CHECK([cat outdata-g0.txt outdata-g1.txt | diff outdata-split.txt - ], [0], [])
240 # Test that the procedure behaves sensibly when presented with
241 # multiple dependent variables
242 AT_SETUP([LINEAR REGRESSION multiple dependent variables])
243 AT_DATA([regression.sps], [dnl
247 compute x0 = rv.normal (0, 1).
248 compute x1 = rv.normal (0, 2).
249 compute err = rv.normal (0, 0.8).
250 compute y = 2 - 1.5 * x0 + 8.4 * x1 + err.
260 /statistics = default.
263 AT_CHECK([pspp -O format=csv regression.sps > output], [0], [ignore])
265 AT_CHECK([head -16 output > first], [0], [])
266 AT_CHECK([tail -16 output > second], [0], [])
268 AT_CHECK([sed -e 's/ycopy/y/g' second | diff first -], [0], [])
273 # Tests the QR decomposition used by the REGRESSION command.
274 AT_SETUP([LINEAR REGRESSION test of QR decomposition])
275 AT_DATA([regression.sps], [dnl
276 data list list / v0 to v1.
278 -12.84099361 0.873270778
279 16.64932538 0.371315664
280 -1.88061907 0.505503722
281 -6.20952354 0.734698282
282 0.33272576 0.891224610
283 -5.54912717 0.052318165
284 6.11832417 0.448853404
285 11.78124974 0.470447593
286 0.75960353 0.565082303
287 6.06432768 0.149316743
288 -2.64919436 0.752532411
289 -10.32250712 0.798263603
290 2.06355038 0.469129797
291 -9.71851742 0.927162270
292 4.65582553 0.250629262
293 9.54574474 0.847032310
294 7.35544368 0.197028541
295 -2.09609740 0.400584261
296 10.30101161 0.671546480
297 -5.24501039 0.929962876
298 1.73412473 0.758161354
299 -3.12732732 0.569785505
300 12.66261501 0.630640223
301 -2.90956805 0.576067804
302 4.89649177 0.624483995
303 13.64613114 0.591089881
304 14.03198397 0.544587572
305 2.23566810 0.967898139
306 5.37367760 0.916246929
307 9.01346888 0.451702743
308 0.75378683 0.235544137
309 -3.47470624 0.742668194
310 -1.02063266 0.860311687
311 -2.67132813 0.082460702
312 23.67661680 0.932553932
313 7.95061359 0.430161125
314 2.05300558 0.066331375
315 -2.01332644 0.163705417
316 20.00663784 0.587292630
317 3.06099417 0.161411889
318 -3.46115358 0.216684625
319 -6.85287183 0.548714855
320 -4.27923809 0.630997663
321 -0.94863395 0.880612945
322 4.47481747 0.359885215
323 -12.80962955 0.886070341
324 9.35753086 0.187176558
325 2.81002235 0.063035095
326 0.01532424 0.964327101
327 0.29867732 0.866408063
328 -2.89035649 0.812135868
329 4.17352811 0.608884061
330 18.15502183 0.920568258
331 -2.92662792 0.550792959
332 -6.08090449 0.965036595
333 -1.09135397 0.862548019
334 7.02816784 0.042277017
335 -21.20245068 0.430673493
336 -8.83397584 0.724976162
337 -0.89055843 0.017934904
338 7.03871587 0.308829557
339 3.84286316 0.685105924
340 4.50280692 0.447635420
341 11.39207346 0.875177896
342 10.86673874 0.518530912
343 7.09853081 0.588367569
344 -12.82864915 0.184667098
345 13.74888760 0.610891139
346 0.37379146 0.557720134
347 -9.79020267 0.942839981
348 0.71574466 0.564570338
349 -17.56040637 0.182061777
350 2.52620466 0.306875011
351 5.37718673 0.366807049
352 -1.83964300 0.465772898
353 6.04848363 0.644501799
354 4.57402403 0.121419591
355 8.55606848 0.373011464
356 -8.46827907 0.491176571
357 -1.77989798 0.734722847
358 -0.68661121 0.540984182
359 1.55798880 0.822587656
360 5.22810831 0.333747878
361 9.50280477 0.068100934
362 -3.74521465 0.248537644
363 1.36045068 0.851827791
364 4.41604088 0.197207162
365 -3.72568327 0.726916693
366 -5.36123334 0.906513529
367 3.61594583 0.414340595
368 -10.01952852 0.140372658
369 25.48681482 0.354309660
370 -3.34529093 0.090075388
371 -18.00437582 0.461438059
372 -5.29782460 0.004362856
373 2.79608522 0.861294398
374 -1.64076209 0.345775481
375 6.82802334 0.137933862
376 -0.45416818 0.404379208
377 -1.66868582 0.797685201
378 -10.02820292 0.075876582
379 5.68232031 0.404815042
380 8.25113850 0.769173748
381 -2.83544237 0.076583474
382 0.87659945 0.092751009
383 6.60270870 0.530444351
384 -12.63924989 0.362099960
385 -6.24451253 0.641993458
386 3.53339015 0.461991892
387 -0.74012232 0.437409755
388 15.37311996 0.974913038
389 -8.09464797 0.543308711
390 -9.61320222 0.221564578
391 0.21843662 0.856512540
392 -1.56958954 0.610709221
393 6.44977372 0.200382138
394 -13.29136274 0.093222309
395 6.46257214 0.024135196
396 -3.82727990 0.601335801
397 0.43081953 0.268230667
398 19.06654416 0.219972815
399 17.02906651 0.996849502
400 -10.18073139 0.012543080
401 12.72088788 0.910600764
402 10.45328185 0.331285901
403 7.14370922 0.896312020
404 -2.81754334 0.048741266
405 6.40217095 0.075796756
406 -3.18030478 0.666325307
407 8.64585957 0.120549153
408 1.37952764 0.899991932
409 -11.81143886 0.601949630
410 0.03899706 0.363808260
411 -10.63828243 0.031092967
412 -6.66940972 0.246204205
413 -5.07374962 0.951272057
414 4.82281566 0.063928187
415 -21.93693564 0.050972680
416 -4.54569883 0.225839693
417 -0.92422779 0.437796785
418 -1.11683029 0.740215139
419 16.77765554 0.851072372
420 9.73614597 0.388180586
421 14.05345168 0.063760129
422 1.20512012 0.665964184
423 8.00307080 0.102447114
424 8.01252623 0.580929209
425 -13.54924183 0.438420739
426 9.87164361 0.970859344
427 17.63437095 0.250501797
428 -3.42503574 0.873290220
429 -2.45873197 0.847756049
430 17.29212092 0.411683187
431 1.15496098 0.530658504
432 -2.14438907 0.592255367
433 -1.79942021 0.517773009
434 -1.30677990 0.830860762
435 1.70233874 0.291826660
436 -3.05532536 0.801767829
437 -4.06732625 0.092294501
438 6.34665476 0.270426235
439 9.46946411 0.196915311
440 14.50919907 0.480357167
441 8.93767237 0.778228613
442 1.90298854 0.903146151
443 18.50500507 0.598561307
444 4.45123027 0.555898218
445 11.37344114 0.616557707
446 -12.14693218 0.409187285
447 18.27198688 0.141619222
448 -5.75939569 0.056989619
449 -4.05515382 0.369281201
450 16.69882098 0.946885257
451 6.39050536 0.679704228
452 4.04213339 0.662792380
453 6.89608366 0.419877433
454 1.56496633 0.358227958
455 5.16679947 0.095144366
456 -3.06280456 0.883265975
457 2.76279175 0.866571973
458 1.84969249 0.264869828
459 21.79840498 0.702650979
460 1.42450528 0.719308635
461 0.96797046 0.111937435
462 18.26840323 0.075621738
463 13.38288377 0.573399086
464 2.41101500 0.766238677
465 3.83866337 0.499888953
466 -1.56577367 0.695244089
467 -0.90342790 0.671654151
468 10.83775583 0.026041124
469 -9.89767935 0.745297991
470 11.74840150 0.309144074
471 1.73069359 0.814063985
472 -5.27966183 0.591005828
473 3.33030043 0.559401806
474 1.31427975 0.520950237
475 -10.04588558 0.507008362
476 10.41228345 0.425867272
477 1.71961097 0.595783108
478 -17.54904427 0.328788939
479 -2.23545419 0.223377350
480 -8.68774333 0.980964240
481 -3.48048220 0.008877675
482 -3.69635326 0.090236718
483 9.76114237 0.769375983
484 -10.25662038 0.508137553
485 0.11155446 0.468504431
486 -8.06824580 0.414098962
487 3.10031660 0.327130207
488 -3.33393146 0.756896774
489 -3.96276749 0.530956360
490 14.53610268 0.846474699
491 1.70505918 0.754662464
492 -1.93495001 0.656650411
493 5.01974522 0.745337633
494 13.41249973 0.489362476
495 11.49288744 0.335924476
496 12.59019763 0.155560469
497 -10.17947298 0.677318449
498 0.05556115 0.655090105
499 3.82092860 0.051838719
500 8.23041456 0.918272190
501 -0.50314649 0.772015826
502 20.05162157 0.880265258
503 8.98816884 0.666646668
504 -6.28312120 0.138534416
505 3.68589909 0.274559458
506 0.59699510 0.253180863
507 -2.74783135 0.983525221
508 0.32515065 0.839969577
509 -3.60606166 0.330646732
510 -0.82037740 0.129591173
511 6.12444860 0.098536516
512 10.95671074 0.033546728
513 -2.84911174 0.720288722
514 6.04597572 0.577061422
515 -0.60147150 0.674096868
516 -5.30458364 0.291468008
517 2.68044943 0.379853840
518 0.85986585 0.984214339
519 -12.77906359 0.882390290
520 7.21420144 0.550884826
521 2.31817022 0.231021556
522 11.60161950 0.888496654
523 -0.19346228 0.242609713
524 5.07478120 0.759161318
525 14.54155003 0.040387654
526 3.81039636 0.874572741
527 2.23233049 0.448317248
528 0.19481869 0.201906051
529 2.81530451 0.132131690
530 12.39893259 0.674693704
531 0.47054642 0.632959494
532 2.16152913 0.734480632
533 0.33398836 0.315024718
534 7.35509037 0.304570986
535 -2.92336559 0.539062343
536 5.79622573 0.392393310
537 -2.37607425 0.403380474
538 0.04498550 0.756875541
539 -1.63674414 0.613789514
540 11.80310547 0.832651469
541 6.30630243 0.850689403
542 1.48394652 0.096243229
543 4.03361865 0.799660045
544 3.54707273 0.408520520
545 2.00327040 0.702944912
546 17.30761707 0.380542812
547 5.72738968 0.105447516
548 -13.64604891 0.328506659
549 8.35976334 0.702173924
550 -7.41197443 0.134396488
551 -15.95683040 0.618526462
552 8.76889573 0.950243069
553 -1.13482624 0.113477080
554 -0.60311407 0.090444247
555 4.95508365 0.612511543
556 5.36934491 0.979213258
557 -0.03554882 0.807185690
558 -11.58131144 0.183341373
559 4.46809041 0.796330582
560 12.49741067 0.346860912
561 8.63824488 0.073684997
562 0.49990913 0.732519306
563 12.82688360 0.109400213
564 13.20375065 0.850369092
565 -8.41110869 0.177717087
566 16.31959963 0.727704840
567 17.59203613 0.235311681
568 0.32148420 0.842195936
569 5.43148331 0.670904647
570 7.14649727 0.028190029
571 0.25410683 0.421535783
572 -12.41047826 0.086404379
573 -10.64180909 0.229659236
574 -6.40185653 0.876365242
575 15.63063324 0.667672536
576 1.94280423 0.799266628
577 -5.76507450 0.367344192
578 8.60895533 0.154109357
579 9.38306751 0.788742770
580 3.43573528 0.284535277
581 4.81848966 0.872283177
582 11.65839314 0.234109111
583 -5.57884822 0.030363060
584 -3.94238060 0.325320686
585 9.38133340 0.201141788
586 -7.65003459 0.647734396
587 11.23091019 0.084927159
588 -6.07705432 0.037273791
589 7.46380750 0.506897136
590 7.42034855 0.869351148
591 -4.43031973 0.231191152
592 -1.07351537 0.480234836
593 -1.40653281 0.690620421
594 -3.82710168 0.990191328
595 5.04583490 0.543427375
596 -11.54265099 0.270542185
597 0.49059479 0.991447248
598 -1.40871469 0.555998766
599 3.64241437 0.743840673
600 -18.30031589 0.357478210
601 4.27487959 0.770619738
602 1.28805821 0.654787106
603 -3.19542768 0.218110139
604 12.53375654 0.011857644
605 11.78889419 0.054127726
606 -5.38392310 0.839309080
607 16.38024181 0.228801038
608 -0.59622631 0.134381782
609 -0.74107258 0.258146632
610 -12.31429450 0.020524447
611 -0.79785028 0.968028764
612 6.39899711 0.038162566
613 7.42024044 0.716163692
614 -3.62470664 0.018201813
615 -2.55049724 0.162446610
616 -10.79888854 0.683070478
617 10.18490144 0.546461234
618 -2.76979044 0.198830067
619 4.85164813 0.094100357
620 0.96477200 0.381801756
621 8.13344336 0.639730450
622 9.04684412 0.786084368
623 10.41746272 0.828304181
624 0.94334368 0.798419831
625 10.13116556 0.191715972
626 -4.12728628 0.575178239
627 -9.59222379 0.876405375
628 1.64680258 0.391003085
629 -4.58897613 0.039176486
630 0.38394379 0.511577564
631 -4.80428215 0.222785463
632 0.35363661 0.681658725
633 -9.63685708 0.183035382
634 3.54363414 0.766127414
635 6.89610808 0.967514568
636 -2.03781105 0.464416752
637 8.67956196 0.421424078
638 -1.09959038 0.061231448
639 7.12587456 0.028601318
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1692 21.72603838 0.442485270
1693 6.10056565 0.418383130
1694 10.48099521 0.333593221
1695 19.28363092 0.382408442
1696 2.12080726 0.601206970
1697 -6.82450704 0.740158518
1698 11.32395692 0.627015570
1699 5.00040701 0.476274658
1700 -11.64750733 0.105099095
1701 5.77442654 0.576560214
1702 0.31340364 0.516479036
1703 -2.09881449 0.146089191
1704 5.12411327 0.368130477
1705 1.70530391 0.621828438
1706 -12.95649749 0.355726301
1707 8.43735652 0.275383759
1708 -15.56161079 0.413160084
1709 5.28942694 0.069125495
1710 5.96040877 0.438716686
1711 -2.59318107 0.571116303
1712 6.95988992 0.650760909
1713 14.00074797 0.623645969
1714 1.66101456 0.558763985
1715 -2.57968349 0.648185379
1716 -5.47584253 0.716901151
1717 6.37222581 0.060563130
1718 2.83664864 0.842419730
1719 1.48926558 0.620280308
1720 0.33471689 0.170312461
1721 5.21648412 0.317639631
1722 0.51733642 0.843867329
1723 9.86005834 0.306036746
1724 -5.81145791 0.975655452
1725 -5.43219061 0.303385368
1726 5.87157118 0.677369776
1727 2.08889926 0.310200439
1728 -2.53433085 0.194730908
1729 7.01359575 0.674259533
1730 -2.00936260 0.682056466
1731 -2.98240739 0.787899917
1732 -7.43289210 0.357483044
1733 -12.58905988 0.981387385
1734 5.78095517 0.533526274
1735 -1.23065889 0.687266774
1736 -6.82309960 0.293249774
1737 8.47000829 0.842056399
1738 -5.81624772 0.303700280
1739 -14.83571031 0.311387926
1740 4.66808472 0.091222946
1741 -2.90144463 0.438301785
1742 10.62458662 0.828335698
1743 7.88002491 0.990156110
1744 10.27680283 0.251087079
1745 -9.42498970 0.292462244
1746 6.73027640 0.213065205
1747 1.28169895 0.353152789
1748 -14.29203733 0.264563048
1749 20.35772711 0.265208837
1750 3.55095071 0.242905653
1751 -17.97067670 0.373951756
1752 10.53141139 0.247520698
1753 0.05293205 0.579940423
1754 12.79674707 0.288031751
1755 -5.44235185 0.075899079
1756 14.29464811 0.960707538
1757 -1.36753291 0.124265178
1758 -4.25946974 0.521720352
1759 -12.46519252 0.385503339
1760 -6.65343143 0.540942219
1761 5.55949184 0.143194404
1762 -1.20480594 0.515905644
1763 -4.13839908 0.164461445
1764 -2.21345425 0.812969725
1765 3.94223380 0.229238952
1766 -10.78661097 0.395049514
1767 3.06997341 0.791234255
1768 24.82205477 0.110859039
1769 6.28791249 0.867125744
1770 -2.80296119 0.703583849
1771 13.24274039 0.425951975
1772 -0.19577471 0.361568727
1773 -2.34894781 0.954814545
1774 19.76339577 0.635462177
1775 -1.87591480 0.149121567
1776 -7.70962391 0.711708342
1777 -2.46291902 0.390902746
1779 regression /variables=v0 v1 /statistics defaults /dependent=v0 /method=enter.
1782 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
1783 Table: Reading free-form data from INLINE.
1788 Table: Model Summary (v0)
1789 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
1793 ,,Sum of Squares,df,Mean Square,F,Sig.
1794 ,Regression,235.23,1,235.23,3.58,.059
1795 ,Residual,98438.40,1498,65.71,,
1796 ,Total,98673.63,1499,,,
1798 Table: Coefficients (v0)
1799 ,,Unstandardized Coefficients,,Standardized Coefficients,,
1800 ,,B,Std. Error,Beta,t,Sig.
1801 ,(Constant),1.24,.42,.00,2.95,.003
1802 ,v1,1.37,.72,.05,1.89,.059
1807 AT_SETUP([LINEAR REGRESSION no crash on all missing])
1808 AT_DATA([regcrash.sps], [dnl
1809 data list list /x * y.
1824 regression /variables=x y /dependent=y.
1827 AT_CHECK([pspp -o pspp.csv regcrash.sps], [1], [ignore], [ignore])
1833 AT_SETUP([LINEAR REGRESSION missing dependent variable])
1835 dnl Test for a bug where missing values in the dependent variable were not being
1836 dnl ignored like they should have been.
1837 AT_DATA([reg-mdv-ref.sps], [dnl
1838 data list notable list / v0 to v2.
1840 0.65377128 7.735648 -23.97588
1841 -0.13087553 6.142625 -19.63854
1842 0.34880368 7.651430 -25.26557
1843 0.69249021 6.125125 -16.57090
1844 -0.07368178 8.245789 -25.80001
1845 -0.34404919 6.031540 -17.56743
1846 0.75981559 9.832291 -28.35977
1847 -0.46958313 5.343832 -16.79548
1848 -0.06108490 8.838262 -29.25689
1849 0.56154863 6.200189 -18.58219
1851 regression /variables=v0 v1
1852 /statistics defaults
1857 AT_CHECK([pspp -o pspp-ref.csv reg-mdv-ref.sps])
1859 AT_DATA([reg-mdv.sps], [dnl
1860 data list notable list / v0 to v2.
1862 0.65377128 7.735648 -23.97588
1863 -0.13087553 6.142625 -19.63854
1864 0.34880368 7.651430 -25.26557
1865 0.69249021 6.125125 -16.57090
1866 -0.07368178 8.245789 -25.80001
1867 -0.34404919 6.031540 -17.56743
1868 0.75981559 9.832291 -28.35977
1869 -0.46958313 5.343832 -16.79548
1870 -0.06108490 8.838262 -29.25689
1871 0.56154863 6.200189 -18.58219
1875 missing values v2 (9).
1877 regression /variables=v0 v1
1878 /statistics defaults
1883 AT_CHECK([pspp -o pspp.csv reg-mdv.sps])
1885 AT_CHECK([diff pspp.csv pspp-ref.csv])
1890 AT_SETUP([LINEAR REGRESSION with invalid syntax (and empty dataset)])
1892 AT_DATA([ss.sps], [dnl
1893 data list notable list / v0 to v2.
1897 regression /variables=v0 v1
1898 /statistics r coeff anova
1903 AT_CHECK([pspp ss.sps], [1], [ignore])
1908 dnl The following example comes from
1909 dnl http://www.ats.ucla.edu/stat/spss/output/reg_spss%28long%29.htm
1910 AT_SETUP([LINEAR REGRESSION coefficient confidence interval])
1912 AT_DATA([conf.sps], [dnl
1915 data list notable list /math female socst read science *
1917 41.00 .00 57.00 57.00 47.00
1918 53.00 1.00 61.00 68.00 63.00
1919 54.00 .00 31.00 44.00 58.00
1920 47.00 .00 56.00 63.00 53.00
1921 57.00 .00 61.00 47.00 53.00
1922 51.00 .00 61.00 44.00 63.00
1923 42.00 .00 61.00 50.00 53.00
1924 45.00 .00 36.00 34.00 39.00
1925 54.00 .00 51.00 63.00 58.00
1926 52.00 .00 51.00 57.00 50.00
1927 51.00 .00 61.00 60.00 53.00
1928 51.00 .00 61.00 57.00 63.00
1929 71.00 .00 71.00 73.00 61.00
1930 57.00 .00 46.00 54.00 55.00
1931 50.00 .00 56.00 45.00 31.00
1932 43.00 .00 56.00 42.00 50.00
1933 51.00 .00 56.00 47.00 50.00
1934 60.00 .00 56.00 57.00 58.00
1935 62.00 .00 61.00 68.00 55.00
1936 57.00 .00 46.00 55.00 53.00
1937 35.00 .00 41.00 63.00 66.00
1938 75.00 .00 66.00 63.00 72.00
1939 45.00 .00 56.00 50.00 55.00
1940 57.00 .00 61.00 60.00 61.00
1941 45.00 .00 46.00 37.00 39.00
1942 46.00 .00 31.00 34.00 39.00
1943 66.00 .00 66.00 65.00 61.00
1944 57.00 .00 46.00 47.00 58.00
1945 49.00 .00 46.00 44.00 39.00
1946 49.00 .00 41.00 52.00 55.00
1947 57.00 .00 51.00 42.00 47.00
1948 64.00 .00 61.00 76.00 64.00
1949 63.00 .00 71.00 65.00 66.00
1950 57.00 .00 31.00 42.00 72.00
1951 50.00 .00 61.00 52.00 61.00
1952 58.00 .00 66.00 60.00 61.00
1953 75.00 .00 66.00 68.00 66.00
1954 68.00 .00 66.00 65.00 66.00
1955 44.00 .00 36.00 47.00 36.00
1956 40.00 .00 51.00 39.00 39.00
1957 41.00 .00 51.00 47.00 42.00
1958 62.00 .00 51.00 55.00 58.00
1959 57.00 .00 51.00 52.00 55.00
1960 43.00 .00 41.00 42.00 50.00
1961 48.00 .00 66.00 65.00 63.00
1962 63.00 .00 46.00 55.00 69.00
1963 39.00 .00 47.00 50.00 49.00
1964 70.00 .00 51.00 65.00 63.00
1965 63.00 .00 46.00 47.00 53.00
1966 59.00 .00 51.00 57.00 47.00
1967 61.00 .00 56.00 53.00 57.00
1968 38.00 .00 41.00 39.00 47.00
1969 61.00 .00 46.00 44.00 50.00
1970 49.00 .00 71.00 63.00 55.00
1971 73.00 .00 66.00 73.00 69.00
1972 44.00 .00 42.00 39.00 26.00
1973 42.00 .00 32.00 37.00 33.00
1974 39.00 .00 46.00 42.00 56.00
1975 55.00 .00 41.00 63.00 58.00
1976 52.00 .00 51.00 48.00 44.00
1977 45.00 .00 61.00 50.00 58.00
1978 61.00 .00 66.00 47.00 69.00
1979 39.00 .00 46.00 44.00 34.00
1980 41.00 .00 36.00 34.00 36.00
1981 50.00 .00 61.00 50.00 36.00
1982 40.00 .00 26.00 44.00 50.00
1983 60.00 .00 66.00 60.00 55.00
1984 47.00 .00 26.00 47.00 42.00
1985 59.00 .00 44.00 63.00 65.00
1986 49.00 .00 36.00 50.00 44.00
1987 46.00 .00 51.00 44.00 39.00
1988 58.00 .00 61.00 60.00 58.00
1989 71.00 .00 66.00 73.00 63.00
1990 58.00 .00 66.00 68.00 74.00
1991 46.00 .00 51.00 55.00 58.00
1992 43.00 .00 31.00 47.00 45.00
1993 54.00 .00 61.00 55.00 49.00
1994 56.00 .00 66.00 68.00 63.00
1995 46.00 .00 46.00 31.00 39.00
1996 54.00 .00 56.00 47.00 42.00
1997 57.00 .00 56.00 63.00 55.00
1998 54.00 .00 36.00 36.00 61.00
1999 71.00 .00 56.00 68.00 66.00
2000 48.00 .00 56.00 63.00 63.00
2001 40.00 .00 41.00 55.00 44.00
2002 64.00 .00 66.00 55.00 63.00
2003 51.00 .00 56.00 52.00 53.00
2004 39.00 .00 56.00 34.00 42.00
2005 40.00 .00 31.00 50.00 34.00
2006 61.00 .00 56.00 55.00 61.00
2007 66.00 .00 46.00 52.00 47.00
2008 49.00 .00 46.00 63.00 66.00
2009 65.00 1.00 61.00 68.00 69.00
2010 52.00 1.00 48.00 39.00 44.00
2011 46.00 1.00 51.00 44.00 47.00
2012 61.00 1.00 51.00 50.00 63.00
2013 72.00 1.00 56.00 71.00 66.00
2014 71.00 1.00 71.00 63.00 69.00
2015 40.00 1.00 41.00 34.00 39.00
2016 69.00 1.00 61.00 63.00 61.00
2017 64.00 1.00 66.00 68.00 69.00
2018 56.00 1.00 61.00 47.00 66.00
2019 49.00 1.00 41.00 47.00 33.00
2020 54.00 1.00 51.00 63.00 50.00
2021 53.00 1.00 51.00 52.00 61.00
2022 66.00 1.00 56.00 55.00 42.00
2023 67.00 1.00 56.00 60.00 50.00
2024 40.00 1.00 33.00 35.00 51.00
2025 46.00 1.00 56.00 47.00 50.00
2026 69.00 1.00 71.00 71.00 58.00
2027 40.00 1.00 56.00 57.00 61.00
2028 41.00 1.00 51.00 44.00 39.00
2029 57.00 1.00 66.00 65.00 46.00
2030 58.00 1.00 56.00 68.00 59.00
2031 57.00 1.00 66.00 73.00 55.00
2032 37.00 1.00 41.00 36.00 42.00
2033 55.00 1.00 46.00 43.00 55.00
2034 62.00 1.00 66.00 73.00 58.00
2035 64.00 1.00 56.00 52.00 58.00
2036 40.00 1.00 51.00 41.00 39.00
2037 50.00 1.00 51.00 60.00 50.00
2038 46.00 1.00 56.00 50.00 50.00
2039 53.00 1.00 56.00 50.00 39.00
2040 52.00 1.00 46.00 47.00 48.00
2041 45.00 1.00 46.00 47.00 34.00
2042 56.00 1.00 61.00 55.00 58.00
2043 45.00 1.00 56.00 50.00 44.00
2044 54.00 1.00 41.00 39.00 50.00
2045 56.00 1.00 46.00 50.00 47.00
2046 41.00 1.00 26.00 34.00 29.00
2047 54.00 1.00 56.00 57.00 50.00
2048 72.00 1.00 56.00 57.00 54.00
2049 56.00 1.00 51.00 68.00 50.00
2050 47.00 1.00 46.00 42.00 47.00
2051 49.00 1.00 66.00 61.00 44.00
2052 60.00 1.00 66.00 76.00 67.00
2053 54.00 1.00 46.00 47.00 58.00
2054 55.00 1.00 56.00 46.00 44.00
2055 33.00 1.00 41.00 39.00 42.00
2056 49.00 1.00 61.00 52.00 44.00
2057 43.00 1.00 51.00 28.00 44.00
2058 50.00 1.00 52.00 42.00 50.00
2059 52.00 1.00 51.00 47.00 39.00
2060 48.00 1.00 41.00 47.00 44.00
2061 58.00 1.00 66.00 52.00 53.00
2062 43.00 1.00 61.00 47.00 48.00
2063 41.00 1.00 31.00 50.00 55.00
2064 43.00 1.00 51.00 44.00 44.00
2065 46.00 1.00 41.00 47.00 40.00
2066 44.00 1.00 41.00 45.00 34.00
2067 43.00 1.00 46.00 47.00 42.00
2068 61.00 1.00 56.00 65.00 58.00
2069 40.00 1.00 51.00 43.00 50.00
2070 49.00 1.00 61.00 47.00 53.00
2071 56.00 1.00 66.00 57.00 58.00
2072 61.00 1.00 71.00 68.00 55.00
2073 50.00 1.00 61.00 52.00 54.00
2074 51.00 1.00 61.00 42.00 47.00
2075 42.00 1.00 41.00 42.00 42.00
2076 67.00 1.00 66.00 66.00 61.00
2077 53.00 1.00 61.00 47.00 53.00
2078 50.00 1.00 58.00 57.00 51.00
2079 51.00 1.00 31.00 47.00 63.00
2080 72.00 1.00 61.00 57.00 61.00
2081 48.00 1.00 61.00 52.00 55.00
2082 40.00 1.00 31.00 44.00 40.00
2083 53.00 1.00 61.00 50.00 61.00
2084 39.00 1.00 36.00 39.00 47.00
2085 63.00 1.00 41.00 57.00 55.00
2086 51.00 1.00 37.00 57.00 53.00
2087 45.00 1.00 43.00 42.00 50.00
2088 39.00 1.00 61.00 47.00 47.00
2089 42.00 1.00 39.00 42.00 31.00
2090 62.00 1.00 51.00 60.00 61.00
2091 44.00 1.00 51.00 44.00 35.00
2092 65.00 1.00 66.00 63.00 54.00
2093 63.00 1.00 71.00 65.00 55.00
2094 54.00 1.00 41.00 39.00 53.00
2095 45.00 1.00 36.00 50.00 58.00
2096 60.00 1.00 51.00 52.00 56.00
2097 49.00 1.00 51.00 60.00 50.00
2098 48.00 1.00 51.00 44.00 39.00
2099 57.00 1.00 61.00 52.00 63.00
2100 55.00 1.00 61.00 55.00 50.00
2101 66.00 1.00 56.00 50.00 66.00
2102 64.00 1.00 71.00 65.00 58.00
2103 55.00 1.00 51.00 52.00 53.00
2104 42.00 1.00 36.00 47.00 42.00
2105 56.00 1.00 61.00 63.00 55.00
2106 53.00 1.00 66.00 50.00 53.00
2107 41.00 1.00 41.00 42.00 42.00
2108 42.00 1.00 41.00 36.00 50.00
2109 53.00 1.00 56.00 50.00 55.00
2110 42.00 1.00 51.00 41.00 34.00
2111 60.00 1.00 56.00 47.00 50.00
2112 52.00 1.00 56.00 55.00 42.00
2113 38.00 1.00 46.00 42.00 36.00
2114 57.00 1.00 52.00 57.00 55.00
2115 58.00 1.00 61.00 55.00 58.00
2116 65.00 1.00 61.00 63.00 53.00
2120 /variables = math female socst read
2121 /statistics = coeff r anova ci (95)
2122 /dependent = science
2126 AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
2127 Table: Model Summary (science)
2128 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2129 ,.699,.489,.479,7.148
2131 Table: ANOVA (science)
2132 ,,Sum of Squares,df,Mean Square,F,Sig.
2133 ,Regression,9543.721,4,2385.930,46.695,.000
2134 ,Residual,9963.779,195,51.096,,
2135 ,Total,19507.500,199,,,
2137 Table: Coefficients (science)
2138 ,,Unstandardized Coefficients,,Standardized Coefficients,,,95% Confidence Interval for B,
2139 ,,B,Std. Error,Beta,t,Sig.,Lower Bound,Upper Bound
2140 ,(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
2141 ,math,.389,.074,.368,5.252,.000,.243,.535
2142 ,female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
2143 ,socst,.050,.062,.054,.801,.424,-.073,.173
2144 ,read,.335,.073,.347,4.607,.000,.192,.479
2151 dnl Checks for regression against bug #44877.
2152 AT_SETUP([LINEAR REGRESSION crash with long string variables])
2153 AT_DATA([regression.sps], [dnl
2156 DATA LIST notable LIST /text (A24) Y * X1 *
2158 V00276601 0.00 90.00
2159 V00292909 10.00 30.00
2160 V00291204 20.00 20.00
2161 V00300070 0.00 90.00
2168 /STATISTICS=COEFF R ANOVA
2173 AT_CHECK([pspp -o pspp.csv regression.sps])
2174 AT_CHECK([cat pspp.csv], [0], [dnl
2175 Table: Model Summary (X1)
2176 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2180 ,,Sum of Squares,df,Mean Square,F,Sig.
2181 ,Regression,3820.45,1,3820.45,16.81,.055
2182 ,Residual,454.55,2,227.27,,
2185 Table: Coefficients (X1)
2186 ,,Unstandardized Coefficients,,Standardized Coefficients,,
2187 ,,B,Std. Error,Beta,t,Sig.
2188 ,(Constant),85.45,10.16,.00,8.41,.004
2189 ,Y,-3.73,.91,-.95,-4.10,.055
2193 V00276601 ,.00,90.00,4.55
2194 V00292909 ,10.00,30.00,-18.18
2195 V00291204 ,20.00,20.00,9.09
2196 V00300070 ,.00,90.00,4.55
2201 dnl Test for a crash which happened on bad input syntax
2202 AT_SETUP([LINEAR REGRESSION -- Empty Parentheses])
2204 AT_DATA([empty-parens.sps], [dnl
2207 data list notable list /math female socst read science *
2209 58.00 1.00 61.00 55.00 58.00
2210 65.00 1.00 61.00 63.00 53.00
2214 /variables = math female socst read
2215 /statistics = coeff r anova ci ()
2216 /dependent = science
2220 AT_CHECK([pspp -o pspp.csv empty-parens.sps], [1], [ignore])
2227 AT_SETUP([LINEAR REGRESSION varibles on ENTER subcommand])
2228 AT_DATA([regression.sps], [dnl
2231 DATA LIST notable LIST /number * value *.
2255 /STATISTICS COEFF R ANOVA
2257 /METHOD=ENTER number.
2261 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
2262 Table: Model Summary (value)
2263 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2264 ,.612,.374,.338,6.176
2266 Table: ANOVA (value)
2267 ,,Sum of Squares,df,Mean Square,F,Sig.
2268 ,Regression,388.065,1,388.065,10.173,.005
2269 ,Residual,648.498,17,38.147,,
2270 ,Total,1036.563,18,,,
2272 Table: Coefficients (value)
2273 ,,Unstandardized Coefficients,,Standardized Coefficients,,
2274 ,,B,Std. Error,Beta,t,Sig.
2275 ,(Constant),.927,2.247,.000,.413,.685
2276 ,number,.611,.192,.612,3.189,.005
2283 AT_SETUP([LINEAR REGRESSION /ORIGIN])
2284 AT_DATA([regression-origin.sps], [dnl
2287 DATA LIST notable LIST /number * value *.
2311 /STATISTICS COEFF R ANOVA
2314 /METHOD=ENTER number.
2318 AT_CHECK([pspp -O format=csv regression-origin.sps], [0], [dnl
2319 Table: Model Summary (value)
2320 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2321 ,.802,.643,.622,6.032
2323 Table: ANOVA (value)
2324 ,,Sum of Squares,df,Mean Square,F,Sig.
2325 ,Regression,1181.726,1,1181.726,32.475,.000
2326 ,Residual,654.989,18,36.388,,
2327 ,Total,1836.715,19,,,
2329 Table: Coefficients (value)
2330 ,,Unstandardized Coefficients,,Standardized Coefficients,,
2331 ,,B,Std. Error,Beta,t,Sig.
2332 ,number,.672,.118,.802,5.699,.000
projects / pspp / blob