一元线性相关与回归.doc

一元线性相关与回归一:资料分析本资料为经正态性检验p1=1.000 ,p2=0.944 可以认为来自正态总体身高与前臂的一 一对应的资料，其相关系数应采用一元线性相关与回归来检验 One-Sample Kolmogorov-Smirnov Test身高前臂长N1111Normal Parametersa,bMean171.9145.45Std. Deviation10.0052.876Most Extreme DifferencesAbsolute.093.159Positive.093.148Negative-.092-.159Kolmogorov-Smirnov Z.308.527Asymp. Sig. (2-tailed)1.000.944a. Test distribution is Normal.b. Calculated from data. 二spss操作过程（1）变量的设置 取变量high表示身高length表示前臂长（2）spss操作过程1.作正态性检验用“one sample kolmogorov_smirnov”的方法分别对high”和“length”进行正态性检验得p1=1.000 ,p2=0.944 可以认为来自正态总体2.相关性与回归a：点击analyzecorrelatebivariate 弹出相应的对话框b：将“high“，”length“分别调入”variable“矩形框，最后点击”ok“键c：analyzeregression弹出相应的对话框，将“high“调入dependent 矩形框，将”length”调入indepent 矩形框d：点击stastics 并激活descriptive continueok三：结果与结论表一 Descriptive StatisticsMeanStd. DeviationN身高171.9110.00511前臂长45.452.87611表二Correlations身高前臂长Pearson Correlation身高1.000.801前臂长.8011.000Sig. (1-tailed)身高.002前臂长.002.N身高1111前臂长1111表三Variables Entered/RemovedbModelVariables EnteredVariables RemovedMethod1前臂长a.Entera. All requested variables entered.b. Dependent Variable: 身高表四ANOVAbModelSum of SquaresdfMean SquareFSig.1Regression641.9811641.98116.097.003aResidual358.929939.881Total1000.90910a. Predictors: (Constant), 前臂长b. Dependent Variable: 身高表五CoefficientsaModelUnstandardized CoefficientsStandardized CoefficientstSig.BStd. ErrorBeta1(Constant)45.28631.6171.432.186前臂长2.786.694.8014.012.003a. Dependent