函数
>
统计
>
描述性统计
> 示例:F 检验
示例:F 检验
使用
Ftest
函数检验两个样本取自方差相同的分布这一假设。
1.
定义数据集并对实验的每个批次创建矢量。
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608.781
569.67
689.556
747.541
618.134
612.182
680.203
607.766
726.232
605.38
518.655
589.226
740.447
588.375
666.83
531.384
710.272
633.417
751.669
619.06
697.979
632.447
708.583
624.256
624.972
575.143
695.07
549.278
769.391
624.972
720.186
587.695
723.657
569.207
703.7
613.257
697.626
565.737
714.98
662.131
657.712
543.177
609.989
512.394
650.771
611.19
707.977
659.982
712.199
569.245
709.631
725.792
703.16
608.96
744.822
586.06
719.217
617.441
619.137
592.845
753.333
631.754
677.933
588.113
735.919
555.724
695.274
702.411
504.167
631.754
693.333
698.254
625
616.791
596.667
551.953
640.898
636.738
720.506
571.551
700.748
521.667
691.604
587.451
636.738
700.422
731.667
595.819
635.079
534.236
716.926
606.188
759.581
575.303
673.903
590.628
736.648
729.314
675.957
619.313
729.23
624.234
697.239
651.304
728.499
724.175
797.662
583.034
668.53
620.227
815.754
584.861
777.392
565.391
712.14
622.506
663.622
628.336
684.181
587.145
629.012
584.319
640.193
538.239
644.156
538.097
642.469
595.686
639.09
648.935
439.418
583.827
614.664
534.905
537.161
569.858
656.773
617.246
659.534
610.337
695.278
584.192
734.04
598.853
687.665
554.774
710.858
605.694
701.716
627.516
382.133
574.522
719.744
582.682
756.82
563.872
690.978
715.962
670.864
616.43
670.308
778.011
660.062
604.255
790.382
571.906
714.75
625.925
716.959
682.426
603.363
707.604
713.796
617.4
444.963
689.576
723.276
676.678
745.527
563.29
778.333
581.879
723.349
447.701
708.229
557.772
681.667
593.537
566.085
632.585
687.448
671.35
597.5
569.53
637.41
581.667
755.864
643.449
692.945
581.593
766.532
494.122
725.663
620.948
698.818
615.903
760
606.667
775.272
579.167
708.885
662.51
727.201
436.237
642.56
644.223
690.773
586.035
688.333
620.833
743.973
652.535
682.461
593.516
761.43
587.451
691.542
570.964
643.392
645.192
697.075
540.079
708.229
707.117
746.467
621.779
744.819
585.777
655.029
703.98
715.224
698.237
614.417
757.12
761.363
621.751
716.106
472.125
659.502
612.7
730.781
583.17
546.928
599.771
734.203
549.227
682.051
605.453
701.341
569.599
759.729
637.233
689.942
621.774
769.424
558.041
715.286
583.17
776.197
345.294
547.099
570.999
619.942
603.232
696.046
595.335
573.109
581.047
638.794
455.878
708.193
627.88
502.825
464.085
632.633
596.129
683.382
640.371
684.812
621.471
738.161
612.727
671.492
606.46
709.771
571.76
685.199
599.304
624.973
579.459
757.363
761.511
633.417
566.969
658.754
654.397
664.666
611.719
663.009
577.409
773.226
576.731
708.261
617.441
739.086
577.409
667.786
548.957
674.481
623.315
695.688
621.761
588.288
553.978
545.61
657.157
752.305
610.882
684.523
552.304
717.159
545.303
721.343
651.934
750.623
635.24
776.488
641.083
750.623
645.321
600.84
566.127
686.196
647.844
687.87
554.815
725.527
620.087
658.796
711.301
690.38
644.355
737.144
713.812
663.851
696.707
766.63
589.453
625.922
634.468
694.43
599.751
730.217
624.542
700.77
723.505
722.242
674.717
763.828
608.539
695.668
612.135
688.887
591.935
531.021
676.656
698.915
647.323
735.905
811.97
732.039
603.883
751.832
608.643
618.663
630.778
744.845
623.063
690.826
472.463
666.893
645.932
759.86
577.176
683.752
567.53
729.591
821.654
730.706
684.49
763.124
600.427
724.193
686.023
630.352
628.109
750.338
605.214
752.417
640.26
707.899
700.767
715.582
665.924
728.746
555.926
591.193
543.299
592.252
511.03
740.833
583.994
786.367
611.048
712.386
623.338
738.333
679.585
741.48
665.004
729.167
655.86
795.833
715.711
723.502
611.999
718.333
577.722
768.08
615.129
747.5
540.316
775
711.667
760.599
639.167
758.333
549.491
682.5
684.167
658.116
672.153
738.213
594.534
681.236
627.65
704.904
551.87
693.623
594.534
624.993
602.66
700.228
585.45
611.874
555.724
579.167
574.934
720.872
584.625
690.32
555.724
677.933
611.874
674.6
698.254
611.999
748.13
530.68
689.942
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Batch
submatrix
cer
1
rows
cer
1
2
3
i
1
rows
cer
batch1
vlookup
1
Batch
1
batch2
vlookup
2
Batch
1
2.
绘制两批数据的图像。
range
i
i
lines
lines
11
range
250
11
batch1
batch2
3.
对数据应用
Ftest
函数。
Ftest
batch1
batch2
f
Var
batch1
Var
batch2
Ftest
所返回的第一个值为 F 统计量。您可以将 F 统计量表中的 F 统计量与表示不同显著性水平的临界值进行比较,以检验该分布是否具有相同方差。
样本具有相同方差的概率为 38%,绝对值形式的 F 统计量等于或大于
f
的当前值。
复制表达式
相关主题
F 检验
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