最新SPSS生物统计分析示例4多因素方差分析Word格式.docx
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最新SPSS生物统计分析示例4多因素方差分析Word格式.docx
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SPSS生物统计分析示例3
(多因素方差分析)
例一:
番薯种植的两因素方差分析
通过SPSS统计分析推断种植密度(因素一)、品种(因素二)对亩产量(鲜重)的影响
数据文件“sweetpotato-wet.sav”
1)方差分析:
Analyze→Generallinearmodel→Univariate…
结果输出:
方差分析表
TestsofBetween-SubjectsEffects
DependentVariable:
每亩鲜产
Source
TypeIIISumofSquares
df
MeanSquare
F
Sig.
CorrectedModel
11407755.723(a)
29
393370.887
3.050
.002
Intercept
149601670.918
1159.757
.000
密度
689784.506
344892.253
2.674
.085
8311710.289
9
923523.365
7.159
密度*品种
2406260.927
18
133681.163
1.036
.453
Error
3869819.834
30
128993.994
Total
164879246.475
60
CorrectedTotal
15277575.557
59
aRSquared=.747(AdjustedRSquared=.502)
无交互效应,密度因素不显著,品种因素极显著
2)多重比较(PostHoc)结果
LSD法:
MultipleComparisons
(I)品种
(J)品种
MeanDifference(I-J)
Std.Error
95%ConfidenceInterval
LowerBound
UpperBound
-350.249541
207.3595866
.102
-773.734313
73.235231
-529.618227(*)
.016
-953.103000
-106.133455
-248.221351
.241
-671.706123
175.263421
486.491070(*)
.026
63.006298
909.975842
-759.726747(*)
.001
-1183.211519
-336.241975
-294.649054
.166
-718.133826
128.835718
222.640273
.292
-200.844499
646.125045
286.248922
.178
-137.235850
709.733694
91.439890
.662
-332.044882
514.924662
350.249541
-73.235231
773.734313
-179.368686
.394
-602.853459
244.116086
102.028190
.626
-321.456582
525.512962
836.740611(*)
413.255839
1260.225383
-409.477206
.058
-832.961978
14.007566
55.600487
.790
-367.884285
479.085259
572.889814(*)
.010
149.405042
996.374586
636.498463(*)
.005
213.013691
1059.983235
441.689431(*)
.041
18.204659
865.174203
529.618227(*)
106.133455
953.103000
179.368686
-244.116086
602.853459
281.396876
.185
-142.087896
704.881648
1016.109297(*)
592.624525
1439.594070
-230.108520
.276
-653.593292
193.376252
234.969173
.266
-188.515599
658.453946
752.258500(*)
328.773728
1175.743272
815.867149(*)
392.382377
1239.351921
621.058117(*)
197.573345
1044.542890
248.221351
-175.263421
671.706123
-102.028190
-525.512962
321.456582
-281.396876
-704.881648
142.087896
734.712421(*)
311.227649
1158.197194
-511.505396(*)
.020
-934.990168
-88.020624
-46.427703
.824
-469.912475
377.057069
470.861624(*)
.031
47.376852
894.346396
534.470273(*)
.015
110.985501
957.955045
339.661241
.112
-83.823531
763.146014
-486.491070(*)
-909.975842
-63.006298
-836.740611(*)
-1260.225383
-413.255839
-1016.109297(*)
-1439.594070
-592.624525
-734.712421(*)
-1158.197194
-311.227649
-1246.217817(*)
-1669.702590
-822.733045
-781.140124(*)
-1204.624896
-357.655352
-263.850797
.213
-687.335569
159.633975
-200.242148
.342
-623.726921
223.242624
-395.051180
.066
-818.535952
28.433592
759.726747(*)
336.241975
1183.211519
409.477206
-14.007566
832.961978
230.108520
-193.376252
653.593292
511.505396(*)
88.020624
934.990168
1246.217817(*)
822.733045
1669.702590
465.077693(*)
.032
41.592921
888.562465
982.367020(*)
558.882248
1405.851792
1045.975669(*)
622.490897
1469.460441
851.166637(*)
427.681865
1274.651410
294.649054
-128.835718
718.133826
-55.600487
-479.085259
367.884285
-234.969173
-658.453946
188.515599
46.427703
-377.057069
469.912475
781.140124(*)
357.655352
1204.624896
-465.077693(*)
-888.562465
-41.592921
517.289327(*)
.018
93.804555
940.774099
580.897976(*)
.009
157.413204
1004.382748
386.088944
.072
-37.395828
809.573716
-222.640273
-646.125045
200.844499
-572.889814(*)
-996.374586
-149.405042
-752.258500(*)
-1175.743272
-328.773728
-470.861624(*)
-894.346396
-47.376852
263.850797
-159.633975
687.335569
-982.367020(*)
-1405.851792
-558.882248
-517.289327(*)
-940.774099
-93.804555
63.608649
.761
-359.876123
487.093421
-131.200383
.532
-554.685155
292.284389
-286.248922
-709.733694
137.235850
-636.498463(*)
-1059.983235
-213.013691
-815.867149(*)
-1239.351921
-392.382377
-534.470273(*)
-957.955045
-110.985501
200.242148
-223.242624
623.726921
-1045.975669(*)
-1469.460441
-622.490897
-580.897976(*)
-1004.382748
-157.413204
-63.608649
-487.093421
359.876123
-194.809032
.355
-618.293804
228.675741
-91.439890
-514.924662
332.044882
-441.689431(*)
-865.174203
-18.204659
-621.058117(*)
-1044.542890
-197.573345
-339.661241
-763.146014
83.823531
395.051180
-28.433592
818.535952
-851.166637(*)
-1274.651410
-427.681865
-386.088944
-809.573716
37.395828
131.200383
-292.284389
554.685155
194.809032
-228.675741
618.293804
Basedonobservedmeans.
*Themeandifferenceissignificantatthe.05level.
0.000**
0.001**
0.026*
0.066
0.213
0.342
0.005**
0.009**
0.015*
0.178
0.355
0.761
0.010**
0.018*
0.031*
0.292
0.532
0.041*
0.072
0.112
0.662
0.016*
0.102
0.166
0.241
0.020*
0.185
0.626
0.824
0.032*
0.266
0.790
0.058
0.394
0.276
黄色阴影为差异极显著(P<
0.01**),绿色阴影为差异显著(P<
0.05*),其余无显著差异
Duncan法:
每亩鲜产
N
Subset
4
5
6
982.982509
1183.224658
1246.833306
1378.033689
1469.473579
1717.694931
1764.122633
1819.723120
1999.091807
2229.200327
.090
.218
.065
.225
.070
Meansforgroupsinhomogeneoussubsetsaredisplayed.
BasedonTypeIIISumofSquares
TheerrortermisMeanSquare(Error)=128993.994.
aUsesHarmonicMeanSampleSize=6.000.
bAlpha=.05.
Duncan
.042
.011
.033
bAlpha=.01.
汇总表:
每亩产率
Alpha=0.01
Alpha=0.05
982.982509
a
A
1183.2
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