1、 单因素方差分析概念单因素方差分析由单一因素影响的一个（或几个相互独立的）因变量，由因素各水平 分组的均值之间的差异，是否有统计意义，并可以进行两两组间的均值比较，称作组 间均值的多重比较，还可以对该因素的若干水平分组中那些组军之间不具有显著性差 异进行分析。2、实例应用用四种饲料喂诸，共 19 头猪分为四组，每组用一种饲料，一段时间后称重量，猪体重增 加数据见 data1-01步骤如下：（2）指定因变量 ：weight ;因素变量：fodder（饲料）单击：Contrasts, 在相应的对话框中指定系数如下， 检验第一组和第四组体重增加的效应是否有显著性差异（1）单因素方差分析按 Analyze → Compare Means→ One-Way AITOVA...单击 Option, 选中描述统计量（3） 输出结果,Descriptiv esNMeanStd. DeviationStd. ErrorA5133.36006.807943.04460B5152.04006.957233.11137C5189.72006.350352.83996D4220.77506.105943.05297Total19171.510534.311377.8715795% Confidence Interval for MeanMinimumMaximumLower BoundUpper Bound124.9068141.8132125.30143.10143.4015160.6785143.80162.70181.8350197.6050182.80198.60211.0591230.4909212.30225.80154.9730188.0481125.30225.80单击 Post Hoc 按钮，选择多重比较的方法One-Tay AHOVA: Post Hoc Bultiple CoMparisons区-Equal Variances AssumedPΓΓΓΓΓLSD Bonferroni Sidak Scheffe R-E-G-WF R-E-G-WflΓ S-N-K ∣- Tukev ∣- T ukev's-b [√ Duncan 厂 Hochberg's GT2 厂 Gabriel厂 Waller-DuncansANOVAweightSum ofSquaresdfMeanSquareFSig.BetweenGroups20538.69836846.233157.467.000Within Groups652.1601543.477Total21190.85818Contrast CoefficientsContrastfodderABCD1100-1Contrast TestsContrastValue of ContrastStd. ErrortdfSig. (2-tailed)weight Assume equal variances 1-87.41504.42321-19.76315.000Does not assume equal1-87.41504.31164-20.2746.852.000variancesMultiple ComparisonsDependent Variable: weight(I) fodder (J) fodderMean Difference (I-J)Std. ErrorSig.95% Confidence IntervalLower BoundUpper BoundLSDABCD-18.68000*-56.36000*-87.41500*4.170244.170244.42321.000.000-27.5687-65.2487-96.8428-9.7913-47.4713-77.9872BA C D18.68000*-37.68000*-68.73500*4.170244.170244.42321.000.0009.7913-46.5687-78.162827.5687-28.7913-59.3072CA B D56.36000*37.68000*4.170244.170244.42321.000.00047.471328.7913-40.482865.248746.5687-21.6272DA B C87.41500*68.73500*4.423214.423214.42321.000.00077.987259.307221.627296.842878.162840.4828Tamhane ABCD-18.68000*-56.36000*-87.41500*4.353184.163534.31164.016.000-33.7633-70.8053-103.1431-3.5967-41.9147-71.6869BA C D18.68000*-37.68000*-68.73500*4.353184.212604.35904.016.0003.5967-52.3109-84.602233.7633-23.0491-52.8678CA B D56.36000*37.68000*4.163534.212604.16966.000.00041.914723.0491-46.405170.805352.3109-15.7049DA B C87.41500*68.73500*4.311644.359044.16966.000.00071.686952.867815.7049103.143184.602246.4051*. The mean difference is significant at the .05 level.
