Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Thu, 14 Dec 2017 14:12:47 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/14/t1513257335hij8rnc6b8fv5m2.htm/, Retrieved Tue, 14 May 2024 02:40:53 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309498, Retrieved Tue, 14 May 2024 02:40:53 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

110

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Multiple Regression] [Regressieanalyse ...] [2017-12-14 13:12:47] [97cb41d201d00a446ae5b9683850817f] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

2	1	0,5231
2	1	0,5450
2	2	0,0994
2	1	0,4474
2	0	0,6307
2	3	-0,3648
2	2	0,1866
2	1	0,3281
2	2	0,1754
2	1	0,3217
2	1	0,5450
2	2	0,0825
2	2	0,1852
2	1	0,4191
2	0	0,5171
2	1	0,4880
2	1	0,1089
2	2	0,0922
2	2	0,1714
2	1	0,5292
2	1	0,3797
2	0	0,5385
2	1	0,5047
2	3	-0,2075
2	1	0,4089
2	1	0,5463
2	1	0,3812
2	1	0,2757
2	1	0,3936
2	1	0,2602
2	0	0,5958
2	3	-0,5942
2	3	-0,1706
2	1	0,3312
2	1	0,4923
2	1	0,1437
2	2	0,0907
2	1	0,4289
2	1	0,2048
2	1	0,1134
2	1	0,2657
2	1	0,3669
2	3	-0,4065
2	3	-0,6649
2	2	0,1890
2	2	0,0212
2	1	0,4046
2	1	0,4588
2	2	0,1816
2	2	0,2280
2	2	-0,0119
2	1	0,3936
2	3	-0,3686
2	2	0,1381
2	2	0,2665
2	1	0,3701
2	2	-0,0023
2	0	0,6232
2	1	0,6206
2	3	-0,4131
2	2	0,2342
2	1	0,3890
2	2	0,2370
2	1	0,3602
2	1	0,2334
2	3	-0,3533
2	0	0,5686
2	3	-0,3026
2	1	0,2052
2	2	-0,1297
2	1	0,1950
2	1	0,4020
2	2	0,2473
2	1	0,2614
2	2	0,1474
2	1	0,2843
2	2	0,0767
2	2	-0,0605
2	2	0,1518
2	3	-0,1936
2	1	0,2349
2	2	0,1610
2	1	0,0984
2	1	0,0812
2	1	0,2190
2	1	0,3834
2	1	0,3570
2	2	-0,0462
2	1	0,1760
2	2	0,1956
2	3	-0,2688
2	2	-0,0926
2	2	-0,0838
2	1	0,2228
2	1	0,1616
2	1	0,1648
2	2	0,0034
2	1	0,0730
2	1	0,3288
2	2	-0,0886
2	1	0,1042
2	2	0,0086
2	2	-0,2450
2	2	0,0499
2	1	0,1935
2	1	0,1632
2	2	0,0311
2	1	0,0929
2	1	0,2498
2	1	0,0488
2	2	-0,0320
2	1	0,0050
2	1	0,1163
2	1	0,1544
2	1	0,0456
2	2	-0,1451
2	3	-0,3164
2	1	0,0869
2	2	0,0117
2	1	-0,0913
2	3	-0,2614
2	2	-0,0560
2	1	-0,0194
2	1	0,2033
2	1	0,3178
2	1	0,2307
2	1	0,2266
2	1	0,1583
2	2	-0,1073
2	2	-0,1274
2	1	0,2167
2	2	0,0168
2	1	0,2971
2	2	0,0149
2	1	0,1180
2	3	-0,2818
2	1	0,2116
2	1	-0,0674
2	1	0,3547
2	1	0,3145
2	1	0,1303
2	2	-0,1091
2	2	-0,0387
2	1	0,2611
2	1	0,3037
2	1	0,2472
2	1	0,1057
2	1	0,1130
2	2	-0,1968
2	1	0,2745
2	1	0,1714
2	1	0,1952
2	1	0,0929
2	2	0,1284
2	1	0,3013
2	2	-0,3177
2	1	0,1161
1	3	-0,5270
1	3	-0,0906
1	2	0,2587
1	2	0,0979
1	2	0,2428
1	2	0,3605
1	3	-0,2615
1	2	0,1583
1	2	0,2424
1	2	0,1584
1	1	0,3561
1	3	-0,1927
1	3	-0,0613
1	2	0,2063
1	2	0,3436
1	2	0,3194
1	2	-0,0845
1	1	0,4403
1	3	-0,2787
1	2	0,2970
1	3	-0,4848
1	2	0,2320
1	3	-0,3061
1	2	0,1446
1	1	0,4758
1	2	-0,0013
1	3	-0,2226
1	3	-0,2083
1	2	0,0862
1	2	0,2098
1	2	0,2666
1	2	0,2516
1	2	0,1699
1	2	-0,0024
1	3	-0,0622
1	2	0,1190
1	2	0,0620
1	3	-0,6904
1	2	0,0743
1	2	0,0730
1	3	-0,4075
1	3	-0,0808
1	3	-0,2974
1	3	-0,4918
1	1	0,3644
1	1	0,3182
1	2	0,2332
1	3	-0,1547
1	3	-0,3698
1	2	0,1843
1	2	0,3568
1	1	0,3496
1	2	0,1227
1	2	0,3361
1	2	0,2182
1	2	0,0371
1	3	-0,2099
1	2	0,3597
2	2	-0,0238
2	2	0,0261
2	2	0,0401
2	2	0,2543
2	1	0,5534
2	2	0,2605
2	3	-0,3435
2	2	0,0467
2	2	0,1283
2	0	0,6467
2	2	-0,0847
2	2	-0,0080
2	3	-0,3479
2	1	0,3558
2	1	0,3831
2	1	0,3942
2	3	-0,4077
2	1	0,4043
2	2	0,3407
2	3	-0,0663
2	2	0,3503
2	1	0,4950
2	1	0,3497
2	2	0,0931
2	3	-0,1524
2	2	0,1355
2	3	-0,1577
2	2	0,2014
2	2	0,0110
2	1	0,5435
2	2	0,0527
2	1	0,6109
2	1	0,5774
2	3	-0,1255
2	2	-0,0679
2	2	0,0528
2	2	-0,0160
2	1	0,5668
2	1	0,4246
2	1	0,3596
2	2	0,2557
2	1	0,5162
2	2	0,2875
2	1	0,4028
2	1	0,3814
2	2	0,2198
2	2	0,0463
2	2	0,1624
2	1	0,4937
2	3	-0,3894
2	1	0,4434
2	2	-0,0640
2	1	0,6187
2	2	0,2644
2	3	-0,1029
2	3	-0,1563
2	2	-0,0789
2	3	-0,4544
2	1	0,4439
2	3	-0,2053
2	1	0,3895
2	1	0,6367
2	2	0,2712
2	1	0,5292
0	2	-0,0412
0	3	-0,1949
0	2	0,0581
0	3	-0,1459
0	3	-0,1076
0	3	-0,1391
0	3	-0,1122
0	2	-0,0660
0	2	0,1389
0	3	-0,2219
0	2	0,2193
0	3	-0,1337
0	1	0,5604
0	1	0,4342
0	1	0,3993
0	2	0,1623
0	3	-0,2995
0	1	0,2825
0	2	0,1293
0	2	0,1486
0	1	0,5319
0	1	0,3116
0	1	0,3521
0	2	0,1707
0	1	0,3869
0	2	0,1626
0	2	0,3188
0	2	0,0276
0	1	0,1824
0	3	-0,4011
0	1	0,4198
0	1	0,1742
0	1	0,3325
0	2	0,1053
0	1	0,4029
0	2	0,1849
0	2	0,0683
0	2	0,2555
0	2	0,0684
0	0	0,5597
0	2	0,2132
0	1	0,2321
0	2	-0,1126
0	0	0,4887
0	2	0,2134
0	2	0,2114
0	3	-0,2381
0	1	0,2630
0	1	0,2860
0	2	0,0171
0	2	0,1407
0	2	0,1733
0	2	0,1558
0	2	-0,0631
0	2	-0,0048
0	1	0,4701
0	1	0,5651
0	2	0,1504
0	2	-0,0021
0	2	0,0549
0	3	-0,2143
0	2	0,0983
0	2	0,0005
0	2	0,1792
0	2	0,1920
0	2	0,1685
0	1	0,3832
0	2	-0,0427
0	1	0,5606
0	2	0,0841
0	1	0,2618
0	1	0,4230
0	1	0,2839
0	1	0,4616
0	2	-0,0158
0	1	0,1611
0	1	0,4772
0	1	0,4335
0	1	0,4172
0	1	0,3517
0	1	0,5083
0	2	-0,0655
0	2	0,0645
0	0	0,5866
0	1	0,5351
0	1	0,4848
0	2	0,2089
0	1	0,4103
0	2	-0,0212
0	1	0,4240
0	0	0,5500
0	2	0,1408
0	1	0,4796
0	2	0,2835
0	2	0,0022
0	1	0,3312
0	3	-0,1140
0	1	0,3434
0	1	0,3028
0	1	0,4168
0	1	0,4772
0	1	0,3695
0	2	-0,0016
0	2	0,0787
0	1	0,2798
0	1	0,5942
0	3	-0,1813
0	3	-0,2211
0	3	-0,4167
0	1	0,3336
0	2	0,2506
0	1	0,3522
0	1	0,4213
0	1	0,5130
0	1	0,2776
0	1	0,4969
0	1	0,2916
0	2	0,2424
0	1	0,4111
0	0	0,6507
0	3	-0,4637
0	2	0,1984
0	1	0,3157
0	2	-0,0314
0	3	-0,1818
0	2	0,2354
0	2	0,1892
0	0	0,5324
0	1	0,5516
0	2	0,2158
0	1	0,2543
0	1	0,3076
0	1	0,4312
0	1	0,4300
0	1	0,3614
0	1	0,6741
0	1	0,3984
0	3	-0,1949
0	1	0,4942
0	0	0,6051
0	1	0,3499
0	1	0,4868
0	1	0,2422
0	2	0,1892
0	2	0,3252
0	0	0,5828
0	1	0,5743
0	3	-0,5352
0	1	0,5198
0	1	0,4462
0	1	0,2251
0	1	0,4167
0	2	0,3393
0	1	0,3297
0	1	0,3814
0	1	0,5686
0	1	0,3391
0	1	0,4708
0	2	-0,0585
0	2	0,1191
0	1	0,2868
0	1	0,2857
0	1	0,2469
0	1	0,2760
0	1	0,2681
0	1	0,5797
0	3	-0,0383
0	1	0,2666
0	1	0,3175
0	2	0,2053
0	1	0,5237
0	2	0,1341
0	2	0,2514
0	2	0,0586
0	3	-0,2218
0	1	0,4833
0	2	0,0854
0	1	0,3942
0	2	0,0725
0	1	0,3395
0	1	0,3621
0	1	0,3605
0	1	0,4553
0	2	-0,0317
0	2	0,2465
0	1	0,4612
0	1	0,3202
0	1	0,5321
0	2	0,0696
0	1	0,5371
0	0	0,5827
0	0	0,5504
0	1	0,3728
0	1	0,2597
0	1	0,2861
0	2	-0,1408
0	1	0,4160
0	2	-0,0640
0	3	-0,1376
0	2	0,2168
0	1	0,3923
0	2	0,1401
0	2	0,2147
0	2	0,2868
0	1	0,4356
0	3	-0,2097
0	2	0,0112
0	3	-0,2479
0	3	-0,2925
0	1	0,4454
0	2	0,1347
0	2	0,1545
0	2	-0,0241
0	2	0,2339
0	1	0,3809
0	1	0,4141
0	1	0,4555
0	1	0,2330
0	2	0,3004
0	2	0,2305
0	2	-0,0249
0	1	0,4927
0	1	0,3191
0	1	0,4386
0	1	0,5716
0	1	0,3862
0	2	-0,0963
0	2	0,0445
0	1	0,4353
0	2	-0,0300
0	1	0,1692
0	1	0,5719
0	1	0,4714
0	1	0,3080
0	2	0,1023
0	2	0,0058
0	1	0,3940
2	2	0,2358
2	1	0,4513
2	2	0,2494
2	0	0,6707
2	1	0,4218
2	1	0,5587
2	3	-0,1953
2	1	0,4411
2	2	0,2334
2	1	0,5648
2	1	0,4075
2	1	0,5408
2	1	0,5280
2	1	0,5123
2	0	0,6973
2	0	0,7011
2	0	0,7356
2	1	0,4353
2	1	0,5183
2	1	0,5084
2	0	0,8170
2	0	0,7403
2	1	0,5378
2	1	0,5132
2	1	0,5616
2	0	0,7533
2	1	0,5878
2	1	0,3458
2	2	0,0150
2	1	0,5418
2	1	0,5108
2	1	0,4973
2	0	0,8566
2	1	0,6265
2	2	0,2593
2	0	0,7095
2	1	0,6134
2	1	0,5439
2	1	0,4349
2	2	0,1125
2	2	0,2243
2	1	0,5057
2	2	0,2167
2	1	0,5203
2	1	0,3293
2	2	-0,0481
2	2	0,1151
2	2	0,1466
2	1	0,3046
2	2	0,1047
2	2	-0,0186
2	2	0,1235
2	2	0,1187
2	2	-0,0200
2	2	0,1935
2	2	0,2770
2	1	0,3552
2	2	0,2011
2	2	0,1527
2	3	-0,4135
2	2	0,3114
2	1	0,3051
2	2	0,0454
2	2	0,2687
2	1	0,3466
2	2	0,0973
2	2	0,2593
2	1	0,4434
2	1	0,4570
2	2	0,2443
2	1	0,4046
2	2	0,0819
2	3	-0,0747
2	2	0,0144
2	2	0,1832
2	2	0,1391
2	2	0,1878
2	2	0,1898
2	2	0,2384
2	2	-0,0999
2	2	0,0532
2	1	0,4425
2	3	-0,1220
2	2	0,3292
2	2	0,2043
2	2	0,0835
2	2	0,0751
2	1	0,3759
2	2	0,1100
2	2	0,1059
2	2	0,2255
2	3	-0,0935
2	2	0,0365
2	2	0,0173
2	2	0,2461
2	2	0,1839
2	2	0,2937
2	2	0,3615
2	2	0,1005
2	2	0,1419
2	2	0,0972
2	1	0,2401
2	2	0,0363
2	2	0,2058
2	2	0,1602
2	2	0,0928
2	2	0,0097
2	2	-0,0327
2	2	0,3470
2	2	-0,0120
2	2	0,1649
2	2	0,0680
2	2	0,2488
2	2	0,2556
2	2	0,2465
2	2	-0,0009
2	2	0,0791
2	2	0,2663
2	2	0,2770
2	1	0,2407
2	2	0,1125
2	2	-0,0243
2	2	0,0879
2	2	0,3416
2	3	-0,1469
2	2	0,1827
2	2	0,2024
2	2	0,2932
2	1	0,2867
2	3	-0,1084
2	2	0,2008
2	2	0,2152
2	2	0,1562
2	2	0,1656
2	2	0,1762
2	2	0,1197
2	2	0,4125
2	2	0,0637
2	2	0,2589
2	1	0,4809
2	2	0,2556
2	2	-0,0286
2	2	0,0547
2	2	0,2150
2	2	0,0086
2	1	0,3579
2	1	0,4697
2	2	0,2743
2	2	0,3501
2	2	0,4227
2	2	0,2886
2	1	0,5032
2	2	0,2461
2	2	0,3715
2	2	0,3744
2	2	0,1625
2	2	0,3767
2	2	0,4350
2	2	0,1491
2	1	0,5103
2	2	0,3703
2	1	0,3666
2	1	0,4820
2	2	0,1395
2	2	0,3847
2	2	0,4103
2	2	0,2274
2	2	0,1785
2	2	0,3597
2	1	0,4092
2	2	0,3961
2	2	0,2588
2	2	0,3761
2	2	0,3029
2	1	0,4939
2	1	0,5006
2	2	0,2819
2	1	0,4787
2	2	0,2935
2	2	0,2919
2	1	0,4995
2	2	0,3704
2	1	0,3731
2	2	0,3290
2	2	0,2054
2	2	0,3197
2	1	0,4846
2	2	0,2776
2	1	0,5748
2	3	-0,0047
2	1	0,4364
2	3	-0,2295
2	1	0,3909
2	2	0,1956
2	3	-0,0194
2	2	0,3668
2	1	0,3833
2	2	0,4237
2	3	-0,0830
2	1	0,5101
2	1	0,4854
2	2	0,2980
2	2	0,3956
2	2	0,2239
2	2	0,3266
2	2	0,3270
2	2	0,3166
2	3	0,0007
2	2	0,2153
2	2	0,0842
2	2	0,3145
2	2	0,3690
2	2	0,3693
2	2	0,3059
2	1	0,4017
2	2	0,4567
2	2	0,4321
2	2	0,2044
2	2	0,0243
2	2	0,1127
2	2	0,0972
2	2	0,3199
2	2	0,1988
2	2	0,1874
2	2	0,1949
2	2	0,4374
2	1	0,3688
2	2	0,1808
2	2	0,0161
2	2	0,0650
2	1	0,4204
2	2	0,3083
2	2	0,3068
2	2	0,2813
2	2	0,2124
2	1	0,4932
2	2	0,3606
2	1	0,4205
2	2	0,1314
2	2	0,1482
2	2	0,0116
2	2	0,0433
2	2	0,0981
2	2	-0,0066
2	3	-0,1158
2	2	-0,0113
2	2	0,0504
2	2	-0,0779
2	2	0,1626
2	2	0,1909
2	2	0,1841
2	2	0,1027
2	2	0,2832
2	2	0,0127
2	3	-0,0991
2	2	0,1141
2	3	-0,0990
2	2	-0,0272
2	2	0,1600
2	3	-0,0469
2	3	-0,1286
2	2	0,1024
2	2	0,1634
2	2	0,1075
2	2	0,0580
2	2	0,0745
2	3	-0,2048
2	2	0,1263
2	2	-0,1385
2	2	0,0572
2	2	-0,0055
2	3	-0,0746
2	2	0,1441
2	2	0,2200
2	2	0,0313
2	2	0,2998
2	2	0,1197
2	2	0,0571
2	2	0,1511
2	2	0,0967
2	2	0,2339
2	2	0,1169
2	3	-0,1262
2	2	0,1914
2	2	0,2467
2	2	0,0838
2	3	-0,1429
2	2	-0,0487
2	3	-0,1035
2	3	-0,2963
2	2	-0,0222
2	2	0,1524
2	2	0,0992
2	2	-0,1521
2	3	-0,1001
2	2	0,0565
2	2	0,1227
2	1	0,5695
2	2	0,1462
2	2	0,2881
2	2	0,2062
2	2	0,0060
2	2	0,3275
2	2	-0,0256
2	2	0,0358
2	2	0,0541
2	2	0,3095
2	2	-0,0281
2	1	0,3915
2	1	0,4215
2	1	0,4068
2	2	0,0372
2	1	0,2922
2	2	0,1452
2	2	-0,0467
2	2	0,1845
2	2	-0,0078
2	2	0,0654
2	2	0,1709
2	2	-0,0264
2	2	0,2876
2	0	0,7260
2	2	-0,0561
2	2	-0,0035
2	2	0,2076
2	2	0,0707
2	2	0,1702
2	2	-0,1042
2	2	0,0625
2	2	0,1307
2	2	0,1138
2	2	-0,0325
2	2	0,0796
2	3	-0,0028
2	2	0,0227
2	3	-0,1203
2	2	0,1068
2	1	0,3360
2	1	0,3175
2	2	0,1086
2	1	0,5038
2	1	0,5019
2	1	0,3273
2	1	0,4183
2	1	0,4220
2	1	0,4325
2	1	0,5820
2	1	0,2403
2	1	0,6175
2	1	0,5956
2	1	0,6002
2	1	0,4538
2	1	0,4977
2	1	0,5876
2	1	0,3226
2	2	0,0621
2	1	0,5848
2	1	0,4540
2	1	0,4010
2	3	-0,1645
2	1	0,4748
2	1	0,5040
2	1	0,3235
2	1	0,4765
2	1	0,5217
2	1	0,4873
2	1	0,3068
2	2	0,3002
2	0	0,6577
2	1	0,5282
2	1	0,5890
2	1	0,6331
2	1	0,6177
2	1	0,4294
2	1	0,5900
2	1	0,4953
2	2	0,2827
2	0	0,7132
2	0	0,6207
2	1	0,2875
2	2	0,2488
2	1	0,5904
2	2	0,2353
2	1	0,6246
2	1	0,5120
2	0	0,6656
2	2	0,1980
2	0	0,6394
2	2	0,1819
2	1	0,5554
2	1	0,3028
2	0	0,6700
2	2	0,2061
2	1	0,2915
2	1	0,4556
2	1	0,4924
2	0	0,6616
2	1	0,3014
2	1	0,5803
2	1	0,3774
2	1	0,3562
2	0	0,6468
2	1	0,4965
2	1	0,3200
2	0	0,5729
2	1	0,6312
2	1	0,3084
2	1	0,5551
2	1	0,5936
2	1	0,4750
2	0	0,6040
2	1	0,4881
2	1	0,4446
2	0	0,6606
2	1	0,3214
2	1	0,5733
2	1	0,4759
2	2	0,2315
2	0	0,5977
2	1	0,4068
2	1	0,5346
2	1	0,3352
2	0	0,6944
2	2	0,2599
2	1	0,5840
2	2	0,0985
2	0	0,6544
2	1	0,5353
2	1	0,5391
2	1	0,5304
2	1	0,6566
2	0	0,7240
2	1	0,3759
2	1	0,5731
2	1	0,4768
2	1	0,4332
2	0	0,7377
2	1	0,5906
2	0	0,6521
2	1	0,5096
2	1	0,3887
2	3	-0,3218
2	1	0,5227
2	1	0,4602
2	1	0,3390
2	1	0,1519
2	1	0,3495
2	2	-0,0695
2	1	0,2298
2	1	0,4458
2	2	0,2153
2	2	0,0633
2	1	0,2512
2	1	0,3216
2	2	-0,1338
2	1	0,3185
2	1	0,3649
2	1	0,4821
2	1	0,2885
2	2	0,2373
2	1	0,2836
2	1	0,2228
2	2	0,1261
2	2	-0,0141
2	1	0,6263
2	1	0,3332
2	1	0,2552
2	1	0,5015
2	0	0,5594
2	2	0,3093
2	1	0,4707
2	2	0,2328
2	1	0,3190
2	3	-0,4065
2	1	0,3116
2	2	0,0676
2	1	0,2182
2	2	-0,2547
2	2	0,0277
2	2	0,0652
2	2	0,2228
2	1	0,4442
2	1	0,3573
2	1	0,2295
2	1	0,4233
2	1	0,4932
2	2	0,0653
2	2	0,1444
2	1	0,3631
2	1	0,2117
2	1	0,2673
2	1	0,2670
2	2	0,1274
2	2	0,2675
2	1	0,2021
2	1	0,3146
2	0	0,7007
2	2	-0,0167
2	1	0,4063
2	1	0,2874
2	1	0,3132
2	2	-0,2778
2	1	0,3593
2	1	0,3856
2	1	0,5210
2	1	0,1625
2	1	0,3936
2	0	0,4861
2	1	0,0677
2	1	0,3877
2	1	0,3640
2	1	0,1427
2	1	0,2879
2	2	0,0931
2	1	0,2429
2	2	-0,0012
2	2	0,0693
2	1	0,1728
2	1	0,3316
2	2	0,2473
2	1	0,2318
2	1	0,4585
2	2	0,1727
2	1	0,3152
2	2	-0,0276
2	1	0,3532
2	1	0,2849
2	1	0,6017
2	2	0,1124
2	2	0,0288
2	2	0,0084
2	2	0,2180
2	2	0,1214
2	2	0,2701
2	1	0,3988
2	1	0,3126
2	1	0,5674
2	1	0,3517
2	1	0,0679
2	2	-0,0523
2	2	0,0887
2	1	0,5404
2	2	0,2373
2	1	0,5689
2	2	-0,0572
2	1	0,5445
2	1	0,2526
2	1	0,3480
2	1	0,2203
2	1	0,4194
2	1	0,4174
2	1	0,3700
2	1	0,3258
2	1	0,2404
2	2	0,1915
2	2	0,2733
2	1	0,3373
2	1	0,3155
2	2	0,1639
2	1	0,4115
2	2	-0,1147
2	2	0,2152
2	1	0,2856
2	1	0,1510
2	1	0,2772
2	2	-0,0587
2	1	0,0868
2	1	0,4418
2	2	0,0304
2	1	0,4184
2	2	0,0241
2	1	0,1674
2	1	0,4101
2	0	0,4000
2	1	0,3160
2	2	0,1296
2	1	0,2233
2	2	0,1055
2	2	0,0968
2	3	-0,1867
2	2	0,1021
2	1	0,1599
2	1	0,3694
2	0	0,4987
2	1	0,2196
2	2	-0,1320
2	1	0,3323
2	1	0,2586
2	1	0,2407
2	1	0,2239
2	0	0,6256
2	1	0,2982
2	2	0,1968
2	0	0,5489
2	2	-0,0093
2	2	0,1667
2	2	0,1118
2	3	-0,5616
2	1	0,3095
2	1	0,3059
2	2	-0,0254
2	1	0,2919
2	2	0,0790
2	1	0,2793
2	1	0,4197
2	1	0,3262
2	1	0,2496
2	2	-0,1734
2	2	-0,1700
2	2	-0,0654
2	2	0,0041
2	1	0,0791
2	2	0,1485
2	1	0,5057
2	1	0,2609
2	2	-0,0055
2	1	0,3165
2	1	0,4142
2	1	0,2477
2	1	0,4644
2	1	0,2535
2	1	0,2367
2	2	0,0828
2	0	0,5047
2	2	0,1395
2	1	0,3597
0	2	-0,1088
0	2	-0,0540
0	3	-0,1839
0	3	-0,1239
0	2	-0,1123
0	2	-0,0896
0	3	-0,1135
0	2	-0,0452
0	2	-0,0786
0	2	-0,0012
0	2	0,0917
0	2	-0,0781
0	2	-0,0227
0	2	-0,0570
0	2	0,0134
0	3	-0,0848
0	1	0,2843
0	2	0,1264
0	2	0,2281
0	2	-0,0471
0	3	-0,6570
0	2	0,1808
0	1	0,3200
0	1	0,4128
0	2	0,2115
0	3	-0,0158
0	2	0,1809
0	2	0,2055
0	1	0,4682
0	2	0,2866
0	3	-0,0950
0	2	0,0678
0	3	-0,3354
0	3	-0,6486
0	2	0,0953
0	1	0,3441
0	2	0,2653
0	2	0,2102
0	2	0,2885
0	2	0,1848
0	2	-0,1043
0	3	-0,4793
0	3	-0,2836
0	3	-0,4726
0	3	-0,1791
0	3	-0,3959
0	3	-0,2317
0	3	-0,4160
0	3	-0,2992
0	3	-0,2776
0	2	-0,2189
0	2	-0,0848
0	3	-0,5375
0	2	-0,1429
2	2	0,1116
2	2	-0,0163
2	2	0,2748
2	2	0,0171
2	2	0,2459
2	2	-0,0006
2	2	0,0872
2	2	0,2446
2	2	-0,0991
2	2	0,0932
2	2	0,1113
2	2	0,2125
2	2	0,0355
2	2	0,1523
2	2	0,1782
2	2	0,1352
2	2	0,1175
2	2	0,0074
2	2	0,1736
2	2	0,1247
2	2	0,0157
2	2	0,1557
2	2	0,0792
2	2	0,2029
2	3	-0,2095
2	2	0,0326
2	2	-0,0582
2	2	0,2011
2	2	0,1428
2	2	0,2851
2	2	0,1382
2	2	0,1180
2	3	-0,1682
2	2	0,2191
2	2	0,0537
2	2	0,0014
2	2	-0,0241
2	2	0,1267
2	3	-0,0364
2	2	0,2291
2	2	0,1884
2	2	0,1070
2	2	-0,0332
2	2	0,1712
2	2	0,1223
2	2	0,1052
2	2	0,2678
2	2	0,2520
2	2	0,1359
2	2	0,0151
2	2	0,0018
2	3	-0,0848
2	2	0,1239
2	2	0,1135
2	2	0,0547
2	2	0,1408
2	1	0,3710
2	2	0,0188
2	2	0,1323
2	2	0,2009
2	3	-0,1128
2	2	0,2008
2	2	-0,0043
2	2	0,1020
2	2	0,0224
2	2	0,0967
2	2	0,1927
2	2	0,1784
2	2	0,2302
2	1	0,4428
2	2	0,0742
2	2	0,0391
2	3	-0,0757
2	2	0,0696
2	2	0,0832
2	2	0,2278
2	2	0,2315
2	2	0,0295
2	2	0,0984
2	2	0,0439
2	3	-0,2829
2	3	-0,3990
2	2	0,1955
2	2	0,0246
2	2	0,0676
2	2	0,1836
2	2	-0,0170
2	2	0,1096
2	2	-0,0176
2	2	-0,0346
2	2	0,2388
2	3	-0,2662
2	2	0,2681
2	2	0,1299
2	2	-0,0514
2	2	0,1248
2	2	0,0503
2	2	0,1316
2	3	-0,0757
2	2	0,1323
2	2	0,1541
2	2	0,0202
2	2	0,1520
2	2	0,1786
2	2	0,1200
2	2	-0,0114
2	2	-0,1178
2	2	0,0409
2	2	0,0099
2	3	-0,2014
2	2	0,0325
2	2	0,1523
2	2	0,1734
2	2	-0,1077
2	2	0,0655
2	2	0,1152
2	2	0,1125
2	2	-0,0098
2	2	-0,0171
2	2	-0,0663
2	2	0,2158
2	3	-0,2067
2	2	0,0901
2	2	0,0540
2	2	0,1529
2	3	-0,0838
2	2	0,1600
2	2	0,1579
2	2	0,2591
2	2	0,1286
2	2	0,1179
2	2	0,1761
2	3	-0,2380
2	2	0,1015
2	2	-0,0062
2	2	0,1392
2	3	-0,0427
2	2	0,0578
2	2	0,2422
2	2	0,0944
2	2	-0,0137
2	2	0,2348
2	2	0,1291
2	2	0,0003
2	3	-0,2779
2	2	0,0945
2	2	0,2242
2	2	0,0783
2	2	-0,0839
2	2	0,2174
2	2	0,3736
2	2	0,2285
2	2	0,2006
2	3	-0,3205
2	2	0,2016
2	2	0,1219
2	2	0,1303
2	2	0,0357
2	2	-0,1211
2	2	0,1595
2	2	0,0238
2	2	0,0490
2	2	0,2031
2	2	0,1326
2	2	0,0343
2	2	0,0832
2	2	0,3266
2	2	-0,0574
2	2	0,2306
2	2	0,0139
2	2	-0,0925
2	1	0,2257
2	2	0,1585
2	2	0,2291
2	2	-0,0655
2	3	-0,2701
2	1	0,2980
2	1	0,3170
2	2	0,0139
2	1	0,3271
2	3	-0,6423
2	1	0,3569
2	2	-0,0452
2	3	-0,2985
2	2	0,1247
2	2	0,2299
2	1	0,4555
2	2	0,2298
2	1	0,2953
2	0	0,5661
2	1	0,4608
2	2	0,1683
2	1	0,4225
2	1	0,2648
2	3	-0,1946
2	3	-0,5290
2	3	-0,3072
2	3	-0,0806
2	1	0,4184
2	1	0,3858
2	2	-0,0329
2	3	-0,0517
2	3	-0,6349
2	1	0,4421
2	3	-0,0778
2	2	0,1830
2	1	0,6141
2	2	0,3145
2	1	0,2631
2	2	0,2141
2	1	0,3333
2	3	-0,2402
2	1	0,3875
2	2	0,1362
2	2	0,2928
2	1	0,3458
2	2	-0,1796
2	2	0,1976
2	2	0,0966
2	1	0,4990
2	1	0,4600
2	3	-0,4322
2	2	0,1277
2	2	0,0115
2	0	0,5382
2	1	0,4964
2	2	0,0471
2	1	0,5224
2	1	0,3255
2	3	-0,1981
2	1	0,5929
2	2	0,2543
2	3	-0,1642
2	1	0,3714
2	1	0,5770
2	1	0,4614
2	3	-0,2856
2	2	-0,1109
2	1	0,2173
2	1	0,3436
2	1	0,3080
2	3	-0,3851
2	1	0,4716
2	2	0,2298
2	2	0,1600
2	3	-0,1989
2	1	0,2706
2	1	0,4688
2	3	-0,2825
2	2	0,1504
2	2	0,1048
2	2	0,0617
2	2	0,1264
2	1	0,2518
2	1	0,3603
2	2	0,1862
2	1	0,3889
2	1	0,5381
2	2	0,1911
2	2	0,2450
2	1	0,4010
2	2	0,0021
2	2	0,0535
2	1	0,4297
2	2	0,2237
2	1	0,2575
2	1	0,3515
2	1	0,3853
2	1	0,3360
2	1	0,3017
2	2	0,2406
2	1	0,3787
2	2	0,1227
2	1	0,4186
2	2	0,0284
2	2	0,0680
2	2	0,1187
2	1	0,3561
2	1	0,3564
2	1	0,2204
2	1	0,4571
2	1	0,3309
2	1	0,2529
2	1	0,2655
2	1	0,4017
2	1	0,4419
2	1	0,1565
2	2	0,1750
2	1	0,3374
2	1	0,2690
2	2	0,2507
2	2	0,3404
2	1	0,3618
2	2	0,1756
2	2	0,1547
2	1	0,3936
2	2	0,1930
2	1	0,3687
2	2	0,0691
2	3	-0,1692
2	1	0,4202
2	2	0,0061
2	2	0,2228
2	1	0,2266
2	1	0,4303
2	2	0,2019
2	1	0,4260
2	2	0,2400
2	2	0,1498
2	2	0,1675
2	1	0,2776
2	1	0,2413
2	2	0,1913
2	1	0,2876
2	1	0,2622
2	1	0,4215
2	1	0,3494
2	1	0,4498
2	2	0,1002
2	1	0,4252
2	2	0,2302
2	2	0,2480
2	1	0,2990
2	2	0,0557
2	1	0,4473
2	2	0,2383
2	2	0,2060
2	1	0,4967
2	1	0,3277
2	2	0,0025
2	1	0,3610
2	1	0,3334
2	1	0,2809
2	2	0,0807
2	2	0,1172
2	1	0,3892
2	1	0,4164
2	1	0,3651
2	2	0,1904
2	1	0,2925
2	2	0,0597
2	2	0,1336
2	1	0,3189
2	2	0,0922
2	2	0,1140
2	1	0,2404
2	1	0,3033
2	2	0,2163
2	1	0,3100
2	2	0,1781
2	1	0,2545
2	2	0,0586
2	3	-0,6138
2	3	-0,0931
2	2	-0,0607
2	1	0,4016
2	1	0,3941
2	2	0,2296
2	1	0,4159
2	1	0,3276
2	1	0,2826
2	2	0,1815
2	2	0,0200
2	1	0,2705
2	1	0,3728
2	1	0,2263
2	1	0,4714
2	1	0,4710
2	3	-0,0441
2	3	0,0455
2	1	0,5387
2	2	0,2881
2	0	0,7825
2	2	0,1628
2	2	0,3382
2	2	0,3383
2	1	0,4018
2	1	0,3175
2	3	-0,2203
2	1	0,6060
2	1	0,4733
2	1	0,3838
2	2	0,1543
2	0	0,8380
2	3	-0,1819
2	1	0,5379
2	1	0,4780
2	2	0,0781
2	2	0,3429
2	1	0,4913
2	2	0,1872
2	2	0,1293
2	1	0,4463
2	1	0,4348
2	1	0,4895
2	1	0,4239
2	1	0,4772
2	2	0,3924
2	3	-0,0587
2	1	0,5111
2	2	0,1972
2	1	0,6113
2	1	0,5724
2	2	0,3193
2	1	0,6950
2	1	0,4473
2	1	0,5021
2	1	0,3673
2	1	0,4704
2	3	-0,1094
2	2	0,1319
2	1	0,3947
2	2	0,1561
2	3	-0,1865
2	1	0,5018
2	1	0,5445
2	2	0,3614
2	1	0,3929
2	1	0,4840
2	2	0,2675
2	1	0,4770
2	1	0,4773
2	2	0,2581
2	1	0,4178
2	1	0,6366
2	0	0,8182
2	0	0,7425
2	0	0,7758
2	1	0,6175
2	1	0,3442
2	1	0,5996
2	1	0,6836
2	1	0,5525
2	2	0,2974
2	1	0,4770
2	1	0,3641
2	1	0,5154
2	0	0,6909
2	1	0,6771
2	1	0,6187
2	1	0,5478
2	1	0,4468
2	1	0,5503
2	1	0,6258
2	2	0,0761
2	1	0,4302
2	1	0,5613
2	1	0,5739
2	1	0,3675
2	2	0,3424
2	2	0,1836
2	1	0,6437
2	1	0,4729
2	1	0,5121
2	1	0,6167
2	1	0,5971
2	2	0,2854
2	1	0,6567
2	1	0,6088
2	1	0,6007
2	0	0,7913
2	1	0,4111
2	1	0,4017
2	1	0,5781
2	1	0,5732
2	0	0,7763
2	1	0,5965
2	1	0,6502
2	0	0,7193
2	1	0,3836
2	2	0,3158
2	2	0,2484
2	1	0,5751
2	1	0,6375
2	1	0,6370
2	1	0,6058
2	1	0,4764
2	2	0,1389
2	1	0,3854
2	0	0,6840
2	1	0,6440
2	1	0,5783
2	0	0,6818
2	1	0,5377
2	1	0,5600
2	1	0,4587
2	1	0,4176
2	1	0,5538
2	2	0,3761
2	1	0,3442
2	1	0,6613
2	1	0,6470
2	1	0,6760
2	1	0,6146
2	1	0,5926
2	1	0,5930
2	1	0,3855
2	0	0,7011
2	2	0,1186
2	2	0,3941
2	1	0,3814
2	1	0,4595
2	1	0,4338
2	0	0,6648
2	1	0,3292
2	0	0,6925
2	1	0,5887
2	1	0,4618
2	0	0,7260
2	2	-0,0245
2	1	0,5230
2	1	0,4401
2	1	0,4744
2	1	0,4316
2	1	0,6376
2	1	0,6106
2	2	0,1650
2	1	0,4612
2	2	-0,0492
2	2	0,2948
2	1	0,5930
2	1	0,5751
2	1	0,5972
2	1	0,4822
2	1	0,5893
2	1	0,5814
2	2	0,3278
2	2	0,1787
2	2	0,2036
2	1	0,4274
2	2	0,1798
2	2	0,0429
2	1	0,4129
2	2	0,1200
2	2	0,0464
2	3	-0,1950
2	2	-0,0264
2	3	-0,1271
2	2	0,0289
2	2	-0,0515
2	2	0,0421
2	3	-0,1211
2	2	-0,0599
2	2	-0,0595
2	2	-0,0449
2	2	-0,0701
2	3	-0,2570
2	2	0,1462
2	3	-0,0673
2	3	-0,4191
2	2	-0,0536
2	3	-0,3551
2	2	0,2099
2	3	-0,2360
2	3	-0,1369
2	2	0,1005
2	2	0,1593
2	2	0,2140
2	3	-0,1161
2	2	0,0669
2	2	0,0434
2	1	0,2995
2	3	-0,1826
2	2	0,2416
2	3	-0,0426
2	1	0,4429
2	1	0,3743
2	3	-0,0590
2	2	0,0437
2	1	0,5009
2	1	0,4306
2	2	-0,0361
2	1	0,3171
2	2	-0,0726
2	3	-0,1890
2	2	0,1894
2	2	0,1133
2	1	0,5966
2	1	0,3653
2	2	0,0548
2	2	0,1098
2	3	-0,2794
2	3	-0,3381
2	2	0,3724
2	1	0,3035
2	3	-0,3090
2	1	0,4118
2	3	-0,4476
2	2	0,0274
2	2	0,3309
2	3	-0,4365
2	2	0,2429
2	2	-0,0426
2	3	-0,4996
2	2	0,2558
2	1	0,5592
2	2	0,1245
0	3	-0,2389
0	1	0,3043
0	3	-0,6671
0	2	-0,0302
0	2	0,1948
0	2	0,0059
0	2	0,0867
0	2	0,1104
0	2	0,1105
0	3	-0,0696
0	2	-0,0484
0	2	0,0423
0	2	0,1564
0	2	0,0423
0	2	-0,1531
0	2	0,0591
0	3	-0,0647
0	2	0,1547
0	2	0,2363
0	2	0,1853
0	1	0,3674
0	2	0,1570
0	2	0,1148
0	3	-0,5099
0	2	0,1860
0	2	0,2129
0	2	0,1152
0	2	-0,0295
0	2	0,0909
0	2	-0,0568
0	3	-0,6613
0	2	-0,0052
0	2	0,1245
0	2	-0,1064
0	2	0,1390
0	2	0,1102
0	2	0,2678
0	2	0,0434
0	2	0,0237
0	2	0,1476
0	3	-0,4466
0	2	-0,0189
0	2	0,1378
0	2	0,0073
0	2	0,0708
0	2	-0,0574
0	2	0,2082
0	2	0,1802
0	2	0,0670
0	2	-0,1181
0	2	0,3001
0	2	-0,0095
0	2	0,0094
0	2	0,1734
0	3	-0,3211
0	3	-0,1145
0	2	0,1173
0	2	0,1310
0	2	0,2227
0	3	-0,1803
0	1	0,3138
0	2	0,2001
0	2	0,2337
0	1	0,4059
0	1	0,2000
0	3	-0,1756
0	1	0,2392
0	1	0,5176
0	2	0,2779
0	3	-0,2353
0	2	0,0053
0	2	0,2121
0	2	0,0060
0	2	0,2347
0	2	0,3463
0	1	0,3587
0	1	0,2988
0	1	0,3923
0	2	0,0350
0	1	0,3548
0	2	-0,0002
0	1	0,3481
0	2	0,1044
0	1	0,3269
0	1	0,2309
0	2	0,0204
0	2	0,2542
0	2	0,0353
0	1	0,3479
0	2	0,2073
0	1	0,4199
0	1	0,4902
0	2	0,1626
0	3	-0,3657
0	3	-0,2240
0	2	0,0862
0	2	0,1082
0	1	0,3621
0	3	-0,0487
0	1	0,3584
0	2	0,0234
0	2	0,1756
0	2	-0,0090
0	3	-0,1754
0	2	0,2881
0	2	0,1283
0	1	0,3026
0	3	-0,2721
0	2	-0,0486
0	2	0,0819
0	1	0,3632
0	2	0,0436
0	1	0,3625
0	2	0,1587
0	2	0,2143
0	2	0,1180
0	1	0,3601
0	2	0,1000
0	2	0,0222
0	1	0,3304
0	1	0,2650
0	3	-0,0365
0	1	0,4643
0	2	0,1424
0	1	0,2916
0	2	0,1652
0	2	0,1208
0	3	-0,2749
0	1	0,3942
0	3	-0,3477
0	2	0,2235
0	2	-0,0276
0	2	0,1783
0	2	0,2014
0	2	0,1829
0	2	0,0685
0	2	0,1516
0	1	0,4889
0	2	-0,0419
0	2	-0,0580
0	2	0,2257
0	1	0,3520
0	1	0,3327
0	2	0,1326
0	2	-0,1080
0	1	0,3992
0	1	0,4039
0	1	0,3585
0	2	0,0347
0	2	0,2124
0	2	0,0782
0	1	0,4087
0	3	-0,1200
0	2	0,0214
0	3	-0,2910
0	2	-0,0889
0	2	0,0597
0	2	0,2454
0	1	0,4189
0	2	0,0675
0	1	0,5479
0	2	0,0540
2	1	0,4432
2	2	0,2366
2	3	-0,0883
2	1	0,6387
2	2	0,3575
2	1	0,5265
2	1	0,4126
2	1	0,3915
2	2	0,2074
2	2	0,2636
2	2	0,3631
2	2	0,2132
2	1	0,3471
2	2	0,1018
2	1	0,4068
2	2	0,4036
2	1	0,5733
2	2	0,1554
2	1	0,5658
2	2	0,2847
2	1	0,4410
2	1	0,3513
2	1	0,3819
2	1	0,5221
2	2	0,2574
2	1	0,4840
2	1	0,3827
2	2	0,2886
2	2	0,4503
2	1	0,3430
2	2	0,0207
2	2	0,1745
2	1	0,4364
2	2	0,3024
2	1	0,3651
2	2	0,2191
2	2	0,0600
2	1	0,3145
2	2	0,3022
2	3	-0,2963
2	2	0,0581
2	1	0,5685
2	3	-0,4319
2	1	0,5802
2	1	0,4111
2	3	-0,0250
2	2	0,3093
2	2	0,1088
2	2	0,2127
2	2	0,2528
2	2	0,3475
2	1	0,3169
2	1	0,4284
2	1	0,2826
2	1	0,3284
2	1	0,3080
2	2	-0,0670
2	3	-0,2731
2	1	0,4849
2	2	-0,0599
2	1	0,2783
2	1	0,3228
2	2	0,0997
2	1	0,2542
2	2	0,0205
2	1	0,4172
2	1	0,4098
2	2	0,0473
2	2	0,1429
2	2	0,2822
2	3	-0,3386
2	1	0,4000
2	2	0,2407
2	2	0,3254
2	2	-0,0706
2	2	0,2657
2	1	0,2598
2	2	-0,0928
2	2	0,2477
2	1	0,2302
2	2	0,2095
2	2	0,2263
2	2	0,1237
2	2	0,0543
2	1	0,4161
2	1	0,2663
2	2	0,0613
2	2	0,3191
2	1	0,3269
2	2	0,0580
2	1	0,5169
2	2	0,1674
2	1	0,2020
2	2	-0,0508
2	1	0,2696
2	2	0,0259
2	2	0,1209
2	1	0,2398
2	1	0,3590
2	2	-0,1268
2	3	-0,2072
2	1	0,2837
2	3	-0,2609
2	2	0,1801
2	2	0,1412
2	2	0,1712
2	1	0,5071
2	1	0,3176
2	2	-0,1068
2	2	-0,0164
2	2	0,1331
2	1	0,2892
2	2	0,1508
2	2	0,1828
2	2	0,0412
2	2	0,2645
2	2	0,0396
2	1	0,2455
2	2	0,0424
2	2	-0,0668
2	1	0,3075
2	1	0,5318
2	2	0,1989
2	2	0,1042
2	2	0,1224
2	2	0,0408
2	2	0,1836
2	1	0,4252
2	2	-0,0166
2	2	-0,1382
2	3	-0,2387
2	2	0,1166
2	1	0,4085
2	1	0,4456
2	2	0,1014
2	1	0,4463
2	2	0,1661
2	2	0,2341
2	2	0,3001
2	2	0,0665
2	2	0,3235
2	1	0,3198
2	0	0,6481
2	1	0,2351
2	0	0,7688
2	1	0,4770
2	1	0,4472
2	1	0,1999
2	1	0,2474
2	1	0,5484
2	1	0,3064
2	2	0,0520
2	1	0,0911
2	0	0,7419
2	1	0,3180
2	1	0,0743
2	2	0,2756
2	1	0,3197
2	1	0,2173
2	1	0,3099
2	1	0,4735
2	1	0,2836
2	0	0,6375
2	0	0,6202
2	1	0,5199
2	1	0,3449
2	1	0,4061
2	1	0,5470
2	1	0,3603
2	1	0,4060
2	0	0,6781
2	1	0,1067
2	1	0,1464
2	1	0,5177
2	1	0,1879
2	1	0,2121
2	1	0,4066
2	0	0,6927
2	1	0,2975
2	1	0,1317
2	1	0,2262
2	1	0,4304
2	1	0,4041
2	1	0,1975
2	1	0,4570
2	1	0,3395
2	2	0,0222
2	0	0,7065
2	1	0,2339
2	1	0,1785
2	1	0,2649
2	2	0,0916
2	1	0,4989
2	1	0,2564
2	1	0,1865
2	2	0,2847
2	2	0,0633
2	1	0,1740
2	1	0,1881
2	1	0,2649
2	1	0,3189
2	1	0,1981
2	1	0,3026
2	1	0,3318
2	1	0,1937
2	0	0,5684
2	1	0,3539
2	1	0,2131
2	1	0,2000
2	1	0,4244
2	0	0,6857
2	1	0,3184
2	1	0,2887
2	1	0,3514
2	1	0,4138
2	1	0,4688
2	1	0,5451
2	0	0,6189
1	1	0,4101
1	3	-0,1791
1	2	0,0133
1	2	-0,1032
1	2	-0,0284
1	2	0,1193
1	1	0,3862
1	2	0,1683
1	2	0,1450
1	2	0,3306
1	2	0,3422
1	1	0,6084
1	1	0,5408
1	3	-0,1507
1	2	0,1205
1	2	0,1898
1	2	0,2660
1	1	0,4668
1	1	0,5824
1	3	-0,1792
1	3	-0,1503
1	2	0,2211
1	1	0,5183
1	2	0,0959
1	1	0,3350
1	3	-0,4501
1	2	0,1150
1	1	0,2804
1	2	0,0184
1	1	0,3154
1	1	0,3345
1	1	0,4233
1	2	0,0362
1	3	-0,0609
1	1	0,4282
1	2	0,1513
0	2	0,3447
0	2	-0,1513
0	1	0,2229
0	2	-0,0272
0	1	0,4681
0	2	0,0662
0	1	0,3277
0	2	0,3271
0	2	-0,0282
0	1	0,2924
0	2	0,0219
0	1	0,3364
0	2	0,0120
0	2	0,0376
0	2	0,0450
0	1	0,2930
0	2	0,2060
0	2	0,1596
0	2	0,2010
0	2	0,1567
0	2	0,2815
0	2	0,0829
0	3	-0,1490
0	2	0,0877
0	3	-0,0842
0	2	-0,0752
0	2	0,2273
0	1	0,4326
0	1	0,5278
0	2	0,0072
0	1	0,3470
0	2	0,1226
0	1	0,3753
0	1	0,4373
0	3	-0,1419
0	2	0,3240
0	2	0,0127
0	2	0,3439
0	2	-0,0262
0	2	-0,0343
0	1	0,3682
0	2	0,2696
0	2	0,0289
0	1	0,4115
0	2	0,0001
0	3	-0,1164
0	2	0,2955
0	2	-0,0107
0	2	0,2078
0	1	0,4393
0	3	-0,6130
0	2	0,1795
0	1	0,4264
0	2	0,0988
0	1	0,4169
0	1	0,2991
0	2	0,2579
0	2	0,2231
0	1	0,3771
0	2	0,2890
0	2	0,2319
0	2	0,1552
0	2	-0,0058
0	2	0,2596
0	2	0,1255
0	2	0,2194
0	2	0,2841
0	3	-0,1890
0	2	-0,1193
0	3	-0,1608
0	3	-0,2750
0	3	-0,1331
0	2	0,1066
0	1	0,3274
0	3	-0,4451
0	1	0,3537
0	3	-0,2848
0	2	0,0727
0	2	0,2157
0	2	0,2290
0	2	0,0080
0	2	0,0488
0	1	0,3031
0	2	0,0007
0	2	0,0374
0	2	-0,0780
0	2	0,0405
0	2	0,0629
0	2	-0,0581
0	2	0,2767
0	2	0,1615
0	3	-0,2402
0	2	0,1271
0	2	0,0863
0	1	0,3365
0	2	0,2287
0	3	-0,2188
0	1	0,2613
0	3	-0,1339
0	2	0,2490
0	2	0,2572
0	2	0,2223
0	3	-0,2619
0	1	0,4511
0	3	-0,1857
0	2	-0,0500
0	3	-0,1631
0	2	0,2613
0	1	0,3829
0	3	-0,3210
0	1	0,4862
0	3	-0,1515
0	1	0,2038
0	1	0,2967
0	2	-0,0169
0	2	0,1146
0	3	-0,3070
0	2	0,3024
2	2	0,2388
2	2	0,1763
2	2	0,0465
2	2	0,2294
2	2	0,1693
2	2	0,1333
2	2	0,1950
2	3	-0,4600
2	1	0,5166
2	1	0,4952
2	2	0,0851
2	2	0,2424
2	3	-0,1037
2	2	0,2365
2	3	-0,1489
2	1	0,3934
2	2	0,2604
2	2	-0,0419
2	2	0,1880
2	3	-0,2711
2	1	0,6048
2	2	0,3042
2	1	0,2907
2	1	0,3866
2	2	0,1886
2	1	0,3491
2	0	0,6427
2	1	0,3144
2	1	0,3786
2	2	0,2985
2	0	0,7644
2	1	0,3810
2	1	0,4225
2	1	0,4180
2	1	0,1767
2	2	0,2085
2	1	0,6166
2	2	0,2160
2	2	0,1449
2	2	0,3201
2	2	0,3236
2	2	0,0826
2	2	0,0611
2	2	0,2536
2	1	0,5236
2	1	0,4789
2	2	0,2101
2	2	0,1165
2	2	0,1552
2	2	0,0533
2	1	0,3567
2	1	0,5215
2	1	0,4234
2	3	-0,0266
2	2	0,1688
2	3	-0,7429
2	2	0,2090
2	1	0,4175
2	1	0,5548
2	3	-0,4819
2	1	0,3929
2	1	0,3040
2	2	0,1413
2	1	0,3828
2	2	0,1725
2	3	-0,1783
2	1	0,1788
2	1	0,2264
2	2	-0,1007
2	2	0,1930
2	1	0,3768
2	1	0,4669
2	1	0,1210
2	1	0,0764
2	1	0,1315
2	1	0,4229
2	1	0,2410
2	1	0,2914
2	1	0,2303
2	2	-0,0075
2	1	0,3566
2	1	0,1772
2	1	0,1373
2	1	0,2904
2	3	-0,1035
2	1	0,0616
2	2	0,0337
2	1	0,1028
2	1	0,2301
2	1	0,2228
2	1	0,2884
2	1	0,0785
2	1	0,1091
2	2	0,0778
2	1	0,3127
2	1	0,3642
2	2	-0,1393
2	1	0,3296
2	2	0,1564
2	1	0,3865
2	2	-0,0944
2	1	0,2271
2	1	0,3359
2	3	-0,1626
2	1	0,3127
2	1	0,1230
2	2	0,0111
2	2	-0,1924
2	2	-0,1580
2	2	-0,1935
2	1	0,3601
2	1	0,4378
2	1	0,2533
2	2	-0,1180
2	2	-0,0359
2	1	0,2034
2	1	0,1251
2	1	0,2653
2	1	0,4219
2	2	0,0275
2	1	0,1046
2	1	0,1715
2	1	0,3407
2	1	0,1705
2	1	0,2608
2	2	0,1256
2	1	0,2210
2	1	0,3081
2	2	0,1757
2	1	0,2122
2	1	0,2016
2	1	0,1723
2	2	-0,0682
2	2	-0,0184
2	1	0,2153
2	1	0,1805
2	1	0,1935
2	1	0,3316
2	1	0,2486
2	1	0,2169
2	2	0,2451
2	1	0,1874
2	1	0,1955
2	1	0,4395
2	3	-0,1568
2	1	-0,0392
2	2	-0,0334
2	1	0,3685
2	1	0,3038
2	1	0,3154
2	2	-0,1697
2	1	0,3587
2	1	0,2431
2	1	-0,0382
2	2	0,0486
2	1	0,3311
2	1	0,3442
2	1	0,1663
2	1	0,1192
2	1	0,4511
2	1	0,3087
2	1	0,4226
2	0	0,7000
2	1	0,3411
2	1	0,4266
2	0	0,6040
2	0	0,6600
2	2	0,2666
2	1	0,5153
2	1	0,5638
2	1	0,5991
2	2	0,1514
2	1	0,4291
2	2	0,1460
2	2	0,3149
2	2	0,1054
2	1	0,4423
2	0	0,6927
2	1	0,5193
2	1	0,2943
2	1	0,3755
2	1	0,3996
2	2	0,0677
2	1	0,5290
2	3	-0,3666
2	0	0,6437
2	1	0,3187
2	1	0,4684
2	2	0,1205
2	1	0,2586
2	0	0,6178
2	3	0,0117
2	1	0,1947
2	0	0,6695
2	1	0,2292
2	1	0,4796
2	1	0,4896
2	1	0,4370
2	1	0,5224
2	1	0,5070
2	1	0,5493
2	0	0,6683
2	0	0,5919
2	1	0,4335
2	1	0,5047
2	1	0,4350
2	1	0,5505
2	1	0,4542
2	1	0,5428
2	1	0,5825
2	1	0,4161
2	1	0,4391
2	1	0,6760
2	1	0,4503
2	1	0,4517
2	3	0,0409
2	0	0,6569
2	2	0,0141
2	1	0,5085
2	1	0,5201
2	1	0,5702
2	1	0,3954
2	1	0,4072
2	1	0,5377
2	3	-0,3313
2	0	0,6074
2	3	-0,4308
2	0	0,5368
2	1	0,5245
2	1	0,5489
2	1	0,4966
2	3	-0,1299
2	1	0,5563
2	1	0,1746
2	1	0,3272
2	1	0,4573
2	1	0,2100
2	1	0,5770
2	1	0,1924
2	2	0,1534
2	1	0,5181
2	1	0,4191
2	2	0,0153
2	0	0,7068
2	2	0,1651
2	1	0,6390
2	1	0,6309
2	0	0,8346
2	1	0,3006
2	1	0,4303
2	0	0,6984
2	1	0,3917
2	1	0,4174
2	1	0,3197
2	1	0,4654
2	1	0,5886
2	1	0,3511
2	1	0,5434
2	0	0,7760
2	1	0,4333
2	0	0,4565
2	2	0,1026
2	1	0,2616
2	0	0,6928
2	1	0,2793
2	2	0,1466
2	0	0,6860
2	1	0,4076
2	3	-0,1010
2	1	0,4219
2	1	0,6329
2	1	0,5398
2	1	0,4274
2	1	0,3338
2	1	0,4749
2	2	0,3129
2	1	0,4314
2	0	0,6782
2	1	0,6582
2	0	0,5869
2	1	0,4879
2	1	0,3024
2	1	0,3380
2	2	-0,0289
2	3	-0,3074
2	2	-0,0797
2	1	0,4771
2	1	0,4391
2	1	0,3373
2	1	0,4085
2	1	0,6374
2	2	-0,0180
2	1	0,4692
2	1	0,5680
2	0	0,6412
2	0	0,7677
2	2	0,3195
2	2	0,0823
2	1	0,3994
2	1	0,5458
2	2	-0,1082
2	1	0,3862
2	1	0,5983
2	1	0,4703
2	1	0,3732
2	1	0,4824
2	1	0,3723
2	1	0,2925
2	0	0,7235
2	1	0,5047
2	1	0,5247
2	0	0,6883
2	1	0,5147
2	1	0,5675
2	1	0,3934
2	1	0,1288
2	0	0,6804
2	1	0,5542
2	1	0,3017
2	3	-0,1928
2	1	0,5358
2	1	0,3212
2	1	0,6619
2	1	0,4124
2	1	0,3938
2	1	0,6410
2	1	0,2113
2	0	0,6235
2	1	0,4990
2	1	0,5046
2	1	0,5704
2	1	0,6403
2	1	0,0725
2	0	0,6662
2	1	0,3288
2	1	0,3416
2	1	0,1139
2	1	0,4144
2	2	0,1437
2	0	0,8418
2	0	0,7432
2	1	0,2775
2	1	0,4341
2	1	0,4072
2	1	0,5601
2	0	0,7185
2	1	0,4366
2	1	0,3285
2	1	0,4816
2	3	-0,2369
2	1	0,4239
2	0	0,6755
2	0	0,6772
2	1	0,6034
2	1	0,2341
2	2	0,0524
2	2	0,2846
2	0	0,8185
2	2	0,1201
2	1	0,5818
2	0	0,6070
2	1	0,4643
2	1	0,3602
2	1	0,1949
2	1	0,3348
2	2	0,2689
2	1	0,5634
2	1	0,5287
2	0	0,6469
2	0	0,6989
2	1	0,3617
2	0	0,7674
2	1	0,4556
2	1	0,5294
2	3	-0,4766
2	0	0,5990
2	0	0,7691
2	1	0,3324
2	1	0,6146
2	1	0,4075
2	2	0,2554
2	1	0,5549
2	1	0,3161
2	1	0,5990
2	0	0,5291
2	1	0,2855
2	1	0,5156
2	3	-0,1430
2	1	0,2878
2	1	0,3095
2	1	0,4155
2	1	0,6901
2	2	0,2190
2	2	0,1886
2	1	0,5129
2	1	0,4187
2	1	0,3241
2	2	0,1110
2	1	0,5204
2	1	0,4781
2	3	-0,1425
2	1	0,3278
2	0	0,6471
2	1	0,4339
2	1	0,4832
2	3	-0,1062
2	2	0,3178
2	1	0,4046
2	1	0,6080
2	1	0,5207
2	1	0,5216
2	0	0,7112
2	0	0,5908
2	3	-0,1502
2	3	-0,5002
2	1	0,6081
2	0	0,7506
2	1	0,6719
2	2	0,1835
2	1	0,5574
2	1	0,6098
2	0	0,7307
2	1	0,6396
2	0	0,7500
2	2	0,0682
2	1	0,6994
2	1	0,6318
2	1	0,6147
2	0	0,7342
2	0	0,7498
2	0	0,6801
2	0	0,7886
2	2	0,2269
2	2	0,2184
2	0	0,7098
2	0	0,7552
2	2	0,0643
2	1	0,4936
2	0	0,7412
2	0	0,7616
2	1	0,4960
2	1	0,6517
2	0	0,5839
2	1	0,4410
0	3	-0,2233
0	3	-0,1848
0	3	-0,0246
0	3	-0,3028
0	2	0,1099
0	3	-0,0851
0	3	-0,1230
0	3	-0,2838
0	3	-0,1192
0	3	-0,0554
0	3	-0,0482
0	3	-0,2518
0	3	-0,3605
0	3	-0,2353
0	2	0,1667
0	2	-0,0208
0	3	-0,3490
0	2	0,1059
0	1	0,3054
0	2	0,2291
0	1	0,3317
0	3	-0,3669
0	1	0,5179
0	2	0,2673
0	2	0,1710
0	1	0,4133
0	1	0,3974
0	1	0,3871
0	1	0,2809
0	3	-0,1750
0	2	-0,0785
0	2	0,0663
0	2	0,2044
0	1	0,3968
0	2	0,0123
0	1	0,3553
0	3	-0,2643
0	2	0,1750
0	3	-0,4532
0	2	0,1487
0	2	0,2585
0	2	0,1618
0	1	0,4967
0	2	-0,0329
0	1	0,3088
0	2	0,2935
0	2	0,1601
0	2	-0,0020
0	2	-0,0231
0	2	0,1509
0	3	-0,1249
0	2	0,0689
0	2	-0,0736
0	2	-0,0335
0	3	-0,3107
0	2	0,2792
0	1	0,2517
0	2	0,1879
0	1	0,2742
0	3	-0,0843
0	1	0,3730
0	3	-0,0930
0	2	0,1502
0	2	0,1728
0	1	0,3693
0	1	0,3009
0	1	0,3140
0	1	0,3421
0	3	-0,1842
0	2	0,1470
0	3	-0,1555
0	1	0,4350
0	2	0,1321
0	2	0,0825
0	2	0,1511
0	1	0,3059
0	2	0,0867
0	2	0,2568
0	2	0,2271
0	2	0,0712
0	2	0,3033
0	2	0,2870
0	2	0,2011
0	1	0,1716
0	3	-0,1542
0	2	0,1218
0	2	0,1877
0	2	0,0950
0	2	0,1023
0	2	0,2408
0	2	0,1322
0	3	0,0935
0	3	-0,0893
0	1	0,3751
0	2	0,1606
0	2	0,2709
0	2	0,0943
0	2	-0,0006
0	1	0,3781
0	3	-0,0461
0	3	-0,2448
0	2	-0,0195
0	2	0,2013
0	2	0,0288
0	2	0,1125
0	2	0,2142
0	2	0,3035
0	1	0,3633
0	3	-0,6245
0	1	0,3117
0	1	0,5569
0	3	-0,2263
0	1	0,4842
0	2	-0,0085
0	2	0,2322
0	2	0,0649
0	2	0,2457
0	2	0,0666
0	2	0,0836
0	2	0,2523
0	3	-0,4137
0	1	0,3109
0	3	-0,0620
0	2	0,1975
0	1	0,4986
0	2	0,0809
0	2	0,2516
0	1	0,3218
0	1	0,3901
0	1	0,3123
0	2	0,0788
0	2	0,2637
0	2	0,2470
0	2	0,2143
0	2	0,0478
0	3	-0,1175
0	3	-0,1230
0	1	0,1658
0	2	0,1897
0	2	0,2427
0	1	0,3355
0	2	0,2917
0	2	0,0093
0	3	-0,0355
0	2	0,1423
0	1	0,1789
0	1	0,3768
0	1	0,3074
1	1	0,4809
1	2	0,2316
1	1	0,3460
1	2	0,2767
1	2	0,0507
1	2	0,0542
1	1	0,4169
1	2	-0,0328
1	2	0,3479
1	2	0,2540
1	1	0,3493
1	1	0,4385
1	1	0,3917
1	2	-0,0624
1	2	0,0405
1	3	-0,2716
1	3	-0,3169
1	2	-0,0446
1	2	0,1471
1	2	0,1083
1	2	0,3247
1	1	0,4036
1	2	-0,0365
1	2	0,2087
1	2	-0,0917
1	2	0,2304
1	2	-0,0241
1	3	-0,3339
1	2	0,0197
1	2	0,0633
1	3	-0,0762
1	2	0,1211
1	2	0,3122
1	3	-0,1325
1	2	0,0684
1	2	0,2686
1	3	-0,0900
1	2	0,0628
1	2	0,2071
2	1	0,2108
2	2	0,2698
2	2	-0,1702
2	2	-0,0081
2	2	-0,0285
2	2	0,1183
2	2	0,1128
2	2	0,0900
2	1	0,4940
2	2	-0,0647
2	2	0,1792
2	1	0,6168
2	2	0,1575
2	1	0,3819
2	2	0,0276
2	1	0,3842
2	2	0,1276
2	2	0,1761
2	2	0,0624
2	2	0,0162
2	1	0,2847
2	2	0,0066
2	2	-0,0556
2	2	0,1392
2	2	0,0907
2	2	-0,2394
2	2	-0,0249
2	1	0,1745
2	1	0,3813
2	2	-0,1294
2	2	0,0399
2	1	0,2167
2	1	0,3301
2	2	0,0678
2	2	0,1557
2	1	0,2169
2	1	0,2088
2	2	0,1867
2	1	0,3293
2	1	0,2564
2	1	0,2210
2	2	0,1421
2	1	0,4851
2	2	0,1368
2	2	0,0865
2	2	0,1960
2	1	0,2177
2	1	0,3327
2	1	0,3422
2	2	0,0898
2	2	-0,0653
2	2	0,0467
2	1	0,3168
2	1	0,2803
2	1	0,1487
2	2	-0,0539
2	3	-0,2733
2	2	0,0141
2	3	-0,2178
2	2	0,1002
2	2	-0,0661
2	2	0,0264
2	2	0,1772
2	2	0,0231
2	2	0,0670
2	2	0,0224
2	3	-0,1171
2	3	-0,3341
2	2	0,2395
2	2	0,0314
2	3	-0,3238
2	2	-0,0506
2	3	-0,0990
2	2	0,2634
2	2	0,2681
2	2	0,0193
2	3	-0,0262
2	2	0,2845
2	3	-0,0597
2	3	-0,1423
2	2	-0,0188
2	3	-0,0895
2	2	0,1403
2	2	0,0605
2	2	-0,0597
2	2	0,0713
2	3	-0,0794
2	3	-0,0568
2	2	0,1351
2	2	0,0348
2	2	0,0544
2	2	0,0817
2	2	0,0760
2	2	0,0976
2	3	-0,6612
2	3	-0,2456
2	2	0,0725
2	2	0,1282
2	2	0,0407
2	2	0,0981
2	1	0,3267
2	2	-0,0813
2	2	-0,0342
2	2	0,0396
2	3	-0,1384
2	2	-0,0043
2	2	0,0420
2	3	0,0359
2	3	-0,1686
2	2	0,0211
2	3	-0,0429
2	2	0,0577
2	2	0,1679
2	2	0,1104
2	2	0,0939
2	2	0,1863
2	3	-0,1575
2	3	-0,0782
2	2	0,1761
2	2	0,1998
2	2	0,0060
2	1	0,4091
2	1	0,3557
2	2	0,1926
2	2	0,1343
2	2	0,0640
2	2	0,0415
2	2	0,1172
2	1	0,6302
2	0	0,6688
2	1	0,3759
2	1	0,5795
2	0	0,6997
2	1	0,3633
2	1	0,4486
2	1	0,4883
2	1	0,6540
2	1	0,3267
2	1	0,6497
2	1	0,3713
2	0	0,6445
2	1	0,5681
2	1	0,4067
2	1	0,4088
2	1	0,5918
2	1	0,3433
2	3	-0,0764
2	1	0,5403
2	1	0,5783
2	1	0,6505

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	33 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time33 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309498&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

33 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309498&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309498&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	33 seconds
R Server	Big Analytics Cloud Computing Center

Multiple Linear Regression - Estimated Regression Equation
ObamaPtKl[t] = + 2.19335 -0.0295863Regio[t] -2.4662PtDiff4[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
ObamaPtKl[t] =  +  2.19335 -0.0295863Regio[t] -2.4662PtDiff4[t]  + e[t] \tabularnewline
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309498&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]ObamaPtKl[t] =  +  2.19335 -0.0295863Regio[t] -2.4662PtDiff4[t]  + e[t][/C][/ROW]
[ROW][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309498&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309498&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
ObamaPtKl[t] = + 2.19335 -0.0295863Regio[t] -2.4662PtDiff4[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	+2.193	0.01454	+1.5080e+02	0	0
Regio	-0.02959	0.008341	-3.5470e+00	0.0003952	0.0001976
PtDiff4	-2.466	0.02789	-8.8410e+01	0	0

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & +2.193 &  0.01454 & +1.5080e+02 &  0 &  0 \tabularnewline
Regio & -0.02959 &  0.008341 & -3.5470e+00 &  0.0003952 &  0.0001976 \tabularnewline
PtDiff4 & -2.466 &  0.02789 & -8.8410e+01 &  0 &  0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309498&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]+2.193[/C][C] 0.01454[/C][C]+1.5080e+02[/C][C] 0[/C][C] 0[/C][/ROW]
[ROW][C]Regio[/C][C]-0.02959[/C][C] 0.008341[/C][C]-3.5470e+00[/C][C] 0.0003952[/C][C] 0.0001976[/C][/ROW]
[ROW][C]PtDiff4[/C][C]-2.466[/C][C] 0.02789[/C][C]-8.8410e+01[/C][C] 0[/C][C] 0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309498&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309498&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	+2.193	0.01454	+1.5080e+02	0	0
Regio	-0.02959	0.008341	-3.5470e+00	0.0003952	0.0001976
PtDiff4	-2.466	0.02789	-8.8410e+01	0	0

Multiple Linear Regression - Regression Statistics
Multiple R	0.8523
R-squared	0.7264
Adjusted R-squared	0.7262
F-TEST (value)	4122
F-TEST (DF numerator)	2
F-TEST (DF denominator)	3105
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.3855
Sum Squared Residuals	461.3

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R &  0.8523 \tabularnewline
R-squared &  0.7264 \tabularnewline
Adjusted R-squared &  0.7262 \tabularnewline
F-TEST (value) &  4122 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 3105 \tabularnewline
p-value &  0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation &  0.3855 \tabularnewline
Sum Squared Residuals &  461.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309498&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C] 0.8523[/C][/ROW]
[ROW][C]R-squared[/C][C] 0.7264[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C] 0.7262[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C] 4122[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]3105[/C][/ROW]
[ROW][C]p-value[/C][C] 0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C] 0.3855[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C] 461.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309498&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309498&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R	0.8523
R-squared	0.7264
Adjusted R-squared	0.7262
F-TEST (value)	4122
F-TEST (DF numerator)	2
F-TEST (DF denominator)	3105
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.3855
Sum Squared Residuals	461.3

Menu of Residual Diagnostics
Description	Link
Histogram	Compute
Central Tendency	Compute
QQ Plot	Compute
Kernel Density Plot	Compute
Skewness/Kurtosis Test	Compute
Skewness-Kurtosis Plot	Compute
Harrell-Davis Plot	Compute
Bootstrap Plot -- Central Tendency	Compute
Blocked Bootstrap Plot -- Central Tendency	Compute
(Partial) Autocorrelation Plot	Compute
Spectral Analysis	Compute
Tukey lambda PPCC Plot	Compute
Box-Cox Normality Plot	Compute
Summary Statistics	Compute

\begin{tabular}{lllllllll}
\hline
Menu of Residual Diagnostics \tabularnewline
Description & Link \tabularnewline
Histogram & Compute \tabularnewline
Central Tendency & Compute \tabularnewline
QQ Plot & Compute \tabularnewline
Kernel Density Plot & Compute \tabularnewline
Skewness/Kurtosis Test & Compute \tabularnewline
Skewness-Kurtosis Plot & Compute \tabularnewline
Harrell-Davis Plot & Compute \tabularnewline
Bootstrap Plot -- Central Tendency & Compute \tabularnewline
Blocked Bootstrap Plot -- Central Tendency & Compute \tabularnewline
(Partial) Autocorrelation Plot & Compute \tabularnewline
Spectral Analysis & Compute \tabularnewline
Tukey lambda PPCC Plot & Compute \tabularnewline
Box-Cox Normality Plot & Compute \tabularnewline
Summary Statistics & Compute \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309498&T=4

[TABLE]
[ROW][C]Menu of Residual Diagnostics[/C][/ROW]
[ROW][C]Description[/C][C]Link[/C][/ROW]
[ROW][C]Histogram[/C][C]Compute[/C][/ROW]
[ROW][C]Central Tendency[/C][C]Compute[/C][/ROW]
[ROW][C]QQ Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Kernel Density Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Skewness/Kurtosis Test[/C][C]Compute[/C][/ROW]
[ROW][C]Skewness-Kurtosis Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Harrell-Davis Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Bootstrap Plot -- Central Tendency[/C][C]Compute[/C][/ROW]
[ROW][C]Blocked Bootstrap Plot -- Central Tendency[/C][C]Compute[/C][/ROW]
[ROW][C](Partial) Autocorrelation Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Spectral Analysis[/C][C]Compute[/C][/ROW]
[ROW][C]Tukey lambda PPCC Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Box-Cox Normality Plot[/C][C]Compute[/C][/ROW]
[ROW][C]Summary Statistics[/C][C]Compute[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309498&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309498&T=4

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Menu of Residual Diagnostics
Description	Link
Histogram	Compute
Central Tendency	Compute
QQ Plot	Compute
Kernel Density Plot	Compute
Skewness/Kurtosis Test	Compute
Skewness-Kurtosis Plot	Compute
Harrell-Davis Plot	Compute
Bootstrap Plot -- Central Tendency	Compute
Blocked Bootstrap Plot -- Central Tendency	Compute
(Partial) Autocorrelation Plot	Compute
Spectral Analysis	Compute
Tukey lambda PPCC Plot	Compute
Box-Cox Normality Plot	Compute
Summary Statistics	Compute

Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted RESET test data: mylm RESET = 28.109, df1 = 2, df2 = 3103, p-value = 7.971e-13
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors RESET test data: mylm RESET = 19.462, df1 = 4, df2 = 3101, p-value = 7.856e-16
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components RESET test data: mylm RESET = 10.631, df1 = 2, df2 = 3103, p-value = 2.505e-05

\begin{tabular}{lllllllll}
\hline
Ramsey RESET F-Test for powers (2 and 3) of fitted values \tabularnewline
> reset_test_fitted
	RESET test
data:  mylm
RESET = 28.109, df1 = 2, df2 = 3103, p-value = 7.971e-13
 \tabularnewline
Ramsey RESET F-Test for powers (2 and 3) of regressors \tabularnewline
> reset_test_regressors
	RESET test
data:  mylm
RESET = 19.462, df1 = 4, df2 = 3101, p-value = 7.856e-16
 \tabularnewline
Ramsey RESET F-Test for powers (2 and 3) of principal components \tabularnewline
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 10.631, df1 = 2, df2 = 3103, p-value = 2.505e-05
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309498&T=5

[TABLE]
[ROW][C]Ramsey RESET F-Test for powers (2 and 3) of fitted values[/C][/ROW]
[ROW][C]> reset_test_fitted
	RESET test
data:  mylm
RESET = 28.109, df1 = 2, df2 = 3103, p-value = 7.971e-13
[/C][/ROW]
[ROW][C]Ramsey RESET F-Test for powers (2 and 3) of regressors[/C][/ROW]
[ROW][C]> reset_test_regressors
	RESET test
data:  mylm
RESET = 19.462, df1 = 4, df2 = 3101, p-value = 7.856e-16
[/C][/ROW]
[ROW][C]Ramsey RESET F-Test for powers (2 and 3) of principal components[/C][/ROW]
[ROW][C]> reset_test_principal_components
	RESET test
data:  mylm
RESET = 10.631, df1 = 2, df2 = 3103, p-value = 2.505e-05
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309498&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309498&T=5

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted RESET test data: mylm RESET = 28.109, df1 = 2, df2 = 3103, p-value = 7.971e-13
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors RESET test data: mylm RESET = 19.462, df1 = 4, df2 = 3101, p-value = 7.856e-16
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components RESET test data: mylm RESET = 10.631, df1 = 2, df2 = 3103, p-value = 2.505e-05

Variance Inflation Factors (Multicollinearity)
> vif Regio PtDiff4 1.037135 1.037135

\begin{tabular}{lllllllll}
\hline
Variance Inflation Factors (Multicollinearity) \tabularnewline
> vif
   Regio  PtDiff4 
1.037135 1.037135 
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309498&T=6

[TABLE]
[ROW][C]Variance Inflation Factors (Multicollinearity)[/C][/ROW]
[ROW][C]> vif
   Regio  PtDiff4 
1.037135 1.037135 
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309498&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309498&T=6

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Variance Inflation Factors (Multicollinearity)
> vif Regio PtDiff4 1.037135 1.037135

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

Figure 7

PNG link

Postscript link

PDF link

Figure 8

PNG link

Postscript link

PDF link

Figure 9

PNG link

Postscript link

PDF link

Figure 10

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = 0 ; par5 = 0 ; par6 = 12 ;

Parameters (R input):

par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = 0 ; par5 = 0 ; par6 = 12 ;

R code (references can be found in the software module):

library(lattice)
library(lmtest)
library(car)
library(MASS)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
mywarning <- ''
par6 <- as.numeric(par6)
if(is.na(par6)) {
par6 <- 12
mywarning = 'Warning: you did not specify the seasonality. The seasonal period was set to s = 12.'
}
par1 <- as.numeric(par1)
if(is.na(par1)) {
par1 <- 1
mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.'
}
if (par4=='') par4 <- 0
par4 <- as.numeric(par4)
if (!is.numeric(par4)) par4 <- 0
if (par5=='') par5 <- 0
par5 <- as.numeric(par5)
if (!is.numeric(par5)) par5 <- 0
x <- na.omit(t(y))
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'Seasonal Differences (s)'){
(n <- n - par6)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+par6,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'First and Seasonal Differences (s)'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
(n <- n - par6)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+par6,j] - x[i,j]
}
}
x <- x2
}
if(par4 > 0) {
x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep='')))
for (i in 1:(n-par4)) {
for (j in 1:par4) {
x2[i,j] <- x[i+par4-j,par1]
}
}
x <- cbind(x[(par4+1):n,], x2)
n <- n - par4
}
if(par5 > 0) {
x2 <- array(0, dim=c(n-par5*par6,par5), dimnames=list(1:(n-par5*par6), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep='')))
for (i in 1:(n-par5*par6)) {
for (j in 1:par5) {
x2[i,j] <- x[i+par5*par6-j*par6,par1]
}
}
x <- cbind(x[(par5*par6+1):n,], x2)
n <- n - par5*par6
}
if (par2 == 'Include Seasonal Dummies'){
x2 <- array(0, dim=c(n,par6-1), dimnames=list(1:n, paste('M', seq(1:(par6-1)), sep ='')))
for (i in 1:(par6-1)){
x2[seq(i,n,par6),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
(k <- length(x[n,]))
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
print(x)
(k <- length(x[n,]))
head(x)
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
sresid <- studres(mylm)
hist(sresid, freq=FALSE, main='Distribution of Studentized Residuals')
xfit<-seq(min(sresid),max(sresid),length=40)
yfit<-dnorm(xfit)
lines(xfit, yfit)
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqPlot(mylm, main='QQ Plot')
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
print(z)
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, mywarning)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Multiple Linear Regression - Ordinary Least Squares', 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
myr <- as.numeric(mysum$resid)
myr
a <-table.start()
a <- table.row.start(a)
a <- table.element(a,'Menu of Residual Diagnostics',2,TRUE)
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Description',1,TRUE)
a <- table.element(a,'Link',1,TRUE)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Histogram',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_histogram.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_centraltendency.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'QQ Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_fitdistrnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Kernel Density Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_density.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Skewness/Kurtosis Test',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Skewness-Kurtosis Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis_plot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Harrell-Davis Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_harrell_davis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Bootstrap Plot -- Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Blocked Bootstrap Plot -- Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'(Partial) Autocorrelation Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_autocorrelation.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Spectral Analysis',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_spectrum.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Tukey lambda PPCC Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_tukeylambda.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Box-Cox Normality Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_boxcoxnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Summary Statistics',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_summary1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable7.tab')
if(n < 200) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' '))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of fitted values',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_fitted <- resettest(mylm,power=2:3,type='fitted')
a<-table.element(a,paste('',RC.texteval('reset_test_fitted'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of regressors',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_regressors <- resettest(mylm,power=2:3,type='regressor')
a<-table.element(a,paste('',RC.texteval('reset_test_regressors'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of principal components',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_principal_components <- resettest(mylm,power=2:3,type='princomp')
a<-table.element(a,paste('',RC.texteval('reset_test_principal_components'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable8.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variance Inflation Factors (Multicollinearity)',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
vif <- vif(mylm)
a<-table.element(a,paste('',RC.texteval('vif'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable9.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code