统计书409页.doc

统计书409页 4Between-Subjects FactorsValue LabelNA因素1a1102a2103a310B因素1b1152b215从左至右是变量名，变变量标签和样本数量Levenes Test of Equality of Error VariancesaDependent Variable:成绩Fdf1df2Sig.599524.701Tests the null hypothesis that the error variance of the dependent variable is equal across groups.a. Design: Intercept + A因素 + B因素 + A因素 * B因素此表是方差齐性检验结果，显著性概率为0.701表示方差在0.05水平差异不显著，即方差齐性Tests of Between-Subjects EffectsDependent Variable:成绩SourceType III Sum of SquaresdfMean SquareFSig.Corrected Model144.267a528.8536.816.000Intercept1888.13311888.133446.016.000A因素101.667250.83312.008.000B因素3.33313.333.787.384A因素 * B因素39.267219.6334.638.020Error101.600244.233Total2134.00030Corrected Total245.86729a. R Squared = .587 (Adjusted R Squared = .501)此表是方差分析结果左上方dependent variable表示因变量成绩，source表示方差来源，corrected model表示条件引起的误差，error表示实验误差 由表可见，A因素的主效应的差异显著，这表明A因素的成绩的等级之间差异显著。B因素差异不显著。两因素的交互作用显著。1. Grand MeanDependent Variable:成绩MeanStd. Error95% Confidence IntervalLower BoundUpper Bound7.933.3767.1588.709总效应的成绩总均值估计值7.933，标准误为0.376，置信区间的下边界为7.158，上边界为8.709。2. A因素Dependent Variable:成绩A因素MeanStd. Error95% Confidence IntervalLower BoundUpper Bounda18.100.6516.7579.443a25.600.6514.2576.943a310.100.6518.75711.443由表可见，A因素三组学生的平均成绩的估计值分别为8.100,5.600,10,100，标准误为0. 651置信区间的下边界分别为6.757,4.257,8.757，商边界为9.433,6.944,11.433。3. B因素Dependent Variable:成绩B因素MeanStd. Error95% Confidence IntervalLower BoundUpper Boundb17.600.5316.5048.696b28.267.5317.1709.363由表可见，B因素二组学生的平均成绩的估计值分别为7.600,8.267，标准误为0. 531置信区间的下边界分别为6. 504, 7.107，商边界为8.696，9. 363。交互作用项的边际均值估计表4. A因素 * B因素Dependent Variable:成绩A因素B因素MeanStd. Error95% Confidence IntervalLower BoundUpper Bounda1b19.200.9207.30111.099b27.000.9205.1018.899a2b15.200.9203.3017.099b26.000.9204.1017.899a3b18.400.9206.50110.299b211.800.9209.90113.699411 8Within-Subjects FactorsMeasure:MEASURE_1测量Dependent Variable1测量12测量23测量3从左至右依次列出一组间因素变量刺激的三个水平，变量标签和样本数量Between-Subjects FactorsN刺激反应142434三个重复测量变量在每种刺激条件下的平均数，标准差和样本数量 描述性统计量Descriptive Statistics刺激反应MeanStd. DeviationN测量11.925.4193422.400.4082431.575.41134Total1.633.732812测量211.100.2160422.825.3686431.600.31624Total1.842.806212测量31.725.1708422.475.3862431.600.54774Total1.600.829012表列出了四种显著性检验统计结果的value值和转换成F分布检验的统计结果。从表中的值看，测量主效应的值由表可见，测量主效应的值都大于0.05，表明测量主效应的贡献模型都不大，交互作用对模型有显著贡献。 重副测量变量间的多元检验Multivariate TestscEffectValueFHypothesis dfError dfSig.测量Pillais Trace.4212.908a2.0008.000.112Wilks Lambda.5792.908a2.0008.000.112Hotellings Trace.7272.908a2.0008.000.112Roys Largest Root.7272.908a2.0008.000.112测量 * 刺激反应Pillais Trace.4181.1894.00018.000.349Wilks Lambda.6191.083a4.00016.000.398Hotellings Trace.555.9714.00014.000.454Roys Largest Root.4071.832b2.0009.000.215a. Exact statisticb. The statistic is an upper bound on F that yields a lower bound on the significance level.c. Design: Intercept + 刺激反应 Within Subjects Design: 测量球形检验Mauchlys Test of SphericitybMeasure:MEASURE_1Within Subjects EffectMauchlys WApprox. Chi-SquaredfSig.EpsilonaGreenhouse-GeisserHuynh-FeldtLower-bound测量.8671.1412.565.8831.000.500Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.a. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.b. Design: Intercept + 刺激反应 Within Subjects Design: 测量组内效应和交互作用的比较Tests of Within-Subjects EffectsMeasure:MEASURE_1SourceType III Sum of SquaresdfMean SquareFSig.测量Sphericity Assumed.4122.2063.255.062Greenhouse-Geisser.4121.765.2333.255.070Huynh-Feldt.4122.000.2063.255.062Lower-bound.4121.000.4123.255.105测量 * 刺激反应Sphericity Assumed.2834.0711.120.378Greenhouse-Geisser.2833.531.0801.120.377Huynh-Feldt.2834.000.0711.120.378Lower-bound.2832.000.1421.120.368Error(测量)Sphericity Assumed1.13818.063Greenhouse-Geisser1.13815.888.072Huynh-Feldt1.13818.000.063Lower-bound1.1389.000.126测量和刺激的交互作用不显著，测量和刺激的主效应也不显著组内因素效应比较Tests of Between-Subjects EffectsMeasure:MEASURE_1Transformed Variable:AverageSourceType III Sum of SquaresdfMean SquareFSig.Intercept103.0231103.023346.079.000刺激反应16.51528.25827.739.000Error2.6799.298三次测量的均值，标准误，置信区间的上下边界值得估计值刺激反应时三次测量结果的边界估计值测量Measure:MEASURE_1测量MeanStd. Error95% Confidence IntervalLower BoundUpper Bound11.633.1191.3641.90321.842.0891.6412.04231.600.1151.3391.861Spss书186练习题1Between-Subjects FactorsValue LabelN方案1方案一602方案二603方案三604方案四60时间130分钟80260分钟80390分钟80从左至右是变量名，变变量标签和样本数量Levenes Test of Equality of Error VariancesaDependent Variable:分数Fdf1df2Sig.1.33311228.207Tests the null hypothesis that the error variance of the dependent variable is equal across groups.a. Design: Intercept + 方案 + 时间 + 方案 * 时间此表是方差齐性检验结果，显著性概率为0.207表示方差在0.05水平差异不显著，即方差齐性Tests of Between-Subjects EffectsDependent Variable:分数SourceType III Sum of SquaresdfMean SquareFSig.Corrected Model43815.103a113983.191126.142.000Intercept1346627.10911346627.10942645.931.000方案11711.37033903.790123.628.000时间28922.669214461.334457.972.000方案 * 时间3181.0656530.17716.790.000Error7199.53822831.577Total1397641.750240Corrected Total51014.641239a. R Squared = .859 (Adjusted R Squared = .852)此表是方差分析结果左上方dependent variable表示因变量成绩，source表示方差来源，corrected model表示条件引起的误差，error表示实验误差 由表可见，A因素的主效应的差异显著，这表明A因素的成绩的等级之间差异显著。B因素差异不显著。两因素的交互作用显著。1. Grand MeanDependent Variable:分数MeanStd. Error95% Confidence IntervalLower BoundUpper Bound74.906.36374.19275.621总效应的成绩总均值估计值74.906，标准误为0.363，置信区间的下边界为74.19，上边界为75.621。70.40880.5672. 方案Dependent Variable:分数方案MeanStd. Error95% Confidence IntervalLower BoundUpper Bound方案一70.408.72568.97971.838方案二80.567.72579.13781.996方案三65.892.72564.46267.321方案四82.758.72581.32984.188由表可见，A因素四组学生的平均成绩的估计值分别为70.40，80.567，65.892,82.758标准误为0. 725置信区间的下边界分别为68.979,79.137,64.462,81.329，商边界为71.838,81.996,67.321,84.1883. 时间Dependent Variable:分数时间MeanStd. Error95% Confidence IntervalLower BoundUpper Bound30分钟61.269.62860.03162.50760分钟75.300.62874.06276.53890分钟88.150.62886.91289.388由表可见，B因素三组学生的平均成绩的估计值分别为61.269, 75.300, 88.150，标准误为0.628置信区间的下边界分别为60. 031, 74.062，86.912商边界为62.507,76.538,89.388交互作用项的边际均值估计表4. 方案 * 时间Dependent Variable:分数方案时间MeanStd. Error95% Confidence IntervalLower BoundUpper Bound方案一30分钟55.4751.25752.99957.95160分钟71.9001.25769.42474.37690分钟83.8501.25781.37486.326方案二30分钟70.7751.25768.29973.25160分钟78.0251.25775.54980.50190分钟92.9001.25790.42495.376方案三30分钟57.4001.25754.92459.87660分钟63.1251.25760.64965.60190分钟77.1501.25774.67479.626方案四30分钟61.4251.25758.94963.90160分钟88.1501.25785.67490.62690分钟98.7001.25796.224101.176均值多重比较表Multiple Comparisons分数LSD(I) 时间(J) 时间Mean Difference (I-J)Std. ErrorSig.95% Confidence IntervalLower BoundUpper Bound30分钟60分钟-14.031*.8885.000-15.782-12.28190分钟-26.881*.8885.000-28.632-25.13160分钟30分钟14.031*.8885.00012.28115.78290分钟-12.850*.8885.000-14.601-11.09990分钟30分钟26.881*.8885.00025.13128.63260分钟12.850*.8885.00011.09914.601Based on observed means. The error term is Mean Square(Error) = 31.577.*. The mean difference is significant at the .05 level.3Within-Subjects FactorsMeasure:MEASURE_1测量Dependent Variable1测量12测量23测量34测量4从左至右依次列出一组间因素变量刺激的三个水平，变量标签和样本数量Between-Subjects FactorsValue LabelN情境1情境1102情境2103情境310三个重复测量变量在每种刺激条件下的平均数，标准差和样本数量描述性统计量Descriptive Statistics情境MeanStd. DeviationN测量1情境115.1000.9944310情境223.20001.0328010情境34.40001.2649110Total14.23337.9032230测量2情境117.6000.9660910情境224.40001.0749710情境38.10001.6633310Total16.70006.9090130测量3情境120.0000.8165010情境225.5000.8498410情境39.20001.5491910Total18.23336.9712930测量4情境120.80001.3165610情境226.2000.7888110情境311.50001.5811410Total19.50006.2958730表列出了四种显著性检验统计结果的value值和转换成F分布检验的统计结果。从表中的值看，测量主效应的值由表可见，测量主效应的值都大于0.05，表明测量主效应的贡献模型都不大，交互作用对模型有显著贡献。 重副测量变量间的多元检验Multivariate TestscEffectValueFHypothesis dfError dfSig.测量Pillais Trace.91590.205a3.00025.000.000Wilks Lambda.08590.205a3.00025.000.000Hotellings Trace10.82590.205a3.00025.000.000Roys Largest Root10.82590.205a3.00025.000.000测量 * 情境Pillais Trace.6434.1056.00052.000.002Wilks Lambda.4284.403a6.00050.000.001Hotellings Trace1.1704.6816.00048.000.001Roys Largest Root1.0058.714b3.00026.000.000a. Exact statisticb. The statistic is an upper bound on F that yields a lower bound on the significance level.c. Design: Intercept + 情境 Within Subjects Design: 测量球形检验Mauchlys Test of SphericitybMeasure:MEASURE_1Within Subjects EffectMauchlys WApprox. Chi-SquaredfSig.EpsilonaGreenhouse-GeisserHuynh-FeldtLower-bound测量.974.6885.984.9821.000.333Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix.a. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.b. Design: Intercept + 情境 Within Subjects Design: 测量组内效应和交互作用的比较Tests of Within-Subjects EffectsMeasure:MEASURE_1SourceType III Sum of SquaresdfMean SquareFSig.测量Sphericity Assumed462.1333154.044106.328.000Greenhouse-Geisser462.1332.945156.911106.328.000Huynh-Feldt462.1333.000154.044106.328.000Lower-bound462.1331.000462.133106.328.000测量 * 情境Sphericity Assumed51.01768.5035.869.000Greenhouse-Geisser51.0175.8908.6615.869.000Huynh-Feldt51.0176.0008.5035.869.000Lower-bound51.0172.00025.5085.869.008Error(测量)Sphericity Assumed117.350811.449Greenhouse-Geisser117.35079.520