统计学实验作业.doc

第一次上级 试验资料的整理与特征数的计算实验目的：熟悉常用统计软件，学习使用excel,spass进行基本特征数的计算实验步骤：（一）次数分布表的编制及统计图制作1、 数据输入（1） 启动Spss，点击varible view 进入定义变量工作表，用name命令定义变量“血清总胆固醇含量”，小数位（decimal）依题意定义为2（2） Date view数据视图工作表输入100例3040岁男子的胆固醇含量2、 求均数、标准差、最大值、最小值和全矩Analyze-Descriptive Statistics-Descriptives选中变量“胆固醇含量”，将其键入varible框内，按optionDescriptivemean，std.deviation、maximum、rangcontinueDescriptiveok输出表3、 分组分10组，依次为2.70、3.15、3.60、4.05、4.50、4.95、5.40、5.85、6.30、6.76、7.20操作如下：（1）transformcomputetarget varible（次数）numeric expression（1）ifcompute varible：if casein culde if case satisfies血清总胆固醇条件表达框输入“=2.70&血清总胆固醇含量=2.70&血清总胆固醇含量=3.15&血清总胆固醇含量3.60”。依次类推，完成10组操作4、 组段标记：Variable view次数，value列的单元格，nonevalue框，变量值代码，value lable框 ，代码所代表内容ok5、 求各组段次数：AnalyzeDescriptive Statisticsfrequenciensvarible框（次数）ok6、 直方图和多边形制作（1） 直方图Graphshistogramvarible框（血清总胆固醇含量）ok（2） Graphsline，simpl，summaries for group of casedefine，other Statisticscategory（血清总胆固醇含量）varible框(次数) ok结果分析某人次数FrequencyPercentValid PercentCumulative PercentValid2.711.01.01.03.1588.08.19.13.6099.09.118.24.052121.021.239.44.502424.024.263.64.951717.017.280.85.4066.06.186.95.8577.07.193.96.3055.05.199.07.2011.01.0100.0Total9999.0100.0MissingSystem11.0Total 参数估计100100.0Descriptive StatisticsNMinimumMaximumMeanStd. DeviationVariance习题2.61001.007.224.7194.92839.862Valid N (listwise)100第二次上级：统计推断，样本平均数的假设检验实验目的：学习使用excel，spass实现样本平均数的假设检验和参数估计 ，理解统计推断的意义实验步骤及结果分析习题4.61、 数据输入（1） 启动spassvariable viewname（桃树枝条含氮量），小数位定义为2（2） Date view（数据输入）2、 统计分析：Analyzecompare meansone-sample t test，test Variable框(桃树枝条含氮量)，test value 框（2.40）ok3、 结果分析One-Sample TestTest Value = 2.40 tdfSig. (2-tailed)Mean Difference95% Confidence Interval of the DifferenceLowerUpper桃树枝条含氮量-.3719.719-.00800-.0567.0407查附表3，df=9，t0.05=2.262,。通过软件得1t10.05,故接受H0：u=u0=2.4%即该测定结果与桃树枝条常规含氮量无差别习题4、81数据输入：variable view定义变量（组别和翅长），小树位数都定义为0，组别取值1表示北方动物，2表示南方动物Date view（数据输入）2、统计分析：Analyzecompare meansindepdent-sample t test，test variablen鸟翅长，grouping variable（组别）define groups：group1:1，group2:2continueok4、 分析结果Independent Samples TestLevenes Test for Equality of Variancest-test for Equality of MeansFSig.tdfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the DifferenceLowerUpper鸟翅长Equal variances assumed.355.561-.14713.886-.2681.825-4.2123.676Equal variances not assumed-.14410.953.888-.2681.865-4.3743.838查附表5，df1=6，df2=7，F0.05=3.87，Fp0.05,两样本鸟翅长的方差是同质的，通过表得到t=-0.147，df=12，t=2.179， t0.05,故接受H0：u1=u2,所以北方动物比南方动物具有较短的附肢这一假说是错误的习题4.91数据输入variable view定义变量（治疗前和治疗后），小数位数都定义为0Date view（数据输入）2、统计分析Analyzecompare means paired-sample t test：paired variable：治疗前-治疗后ok3、结果分析Paired Samples TestPaired DifferencestdfSig. (2-tailed)MeanStd. DeviationStd. Error Mean95% Confidence Interval of the DifferenceLowerUpperPair 1习题4.9 - 治疗后19.92312.5993.49412.30927.5375.70112.000查附表3，df=12，t0.05=2.179，tt0.05,故pp0.05,否定H0：u1=u2，接受HA：u1u2，该药不具有降血压的作用习题4.101数据输入variable view定义变量（病毒A和病毒B），小数位数都定义为0Date view（数据输入）2、统计分析Analyzecompare means paired-sample t test：paired variable：病毒A-病毒Bok3、结果分析Paired Samples TestPaired DifferencestdfSig. (2-tailed)MeanStd. DeviationStd. Error Mean95% Confidence Interval of the DifferenceLowerUpperPair 1习题4.10 - 病毒b4.0004.3091.524.3977.6032.6257.034查附表3，df=7，t0.05=2.365，tt0.05,故pp0.05,否定H0：u1=u2，接受HA：u1u2，说明两种病毒的致病能力有显著差异第三次上级：卡方检验实验目的：熟悉卡方检验原理，掌握卡方检验的实现方法实验步骤及结果分析习题5、31、数据输入variable view定义变量（性别与只数），小数位数都定义为0Date view（数据输入）2、统计分析Dateweight case by：frequency variable：只数okAnalyzenonparametricx2statistics：chi-squarecontiuevalue（1：1）ok3、结果分析Test Statistics数量Chi-Square5.881adf1Asymp. Sig.015Exact Sig.019Point Probability.007a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 71.5.据附表4查到，df=1，x20.05=3.84，x2x20.05，故pp0.05,否定H0，接受HA，野兔的性别比例不符合1:1习题5、41、数据输入variable view定义变量（芒性状表型和株数），小数位数都定义为0Date view（数据输入）2、统计分析Dateweight case by：frequency variable：株数okAnalyzenonparametricx2statistics：chi-squarecontiuevalue（3:4:9）ok3、结果分析Test Statistics数量Chi-Square.041adf2Asymp. Sig.980Exact Sig.980Point Probability.003a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 116.3.附表4df=2，x20.05=5.99，x20.041p0.05,接受H0，F2代的芒性状表型的试验比率符合9:3:4的理论比率习题5.51、数据输入variable view定义变量（性别和人数），小数位数都定义为0Date view（数据输入）2、统计分析Dateweight case by：frequency variable：人数okAnalyzenonparametric testx2exactNo.3statistics：chi-squarecontiuevalue（1:1）ok3、结果分析Test Statistics数量Chi-Square.041adf2Asymp. Sig.980Exact Sig.980Point Probability.003a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 116.3.附表4，df=1，x20.05=,3.84，x2x2 0.05，故p0.05,故接受H0，即红星苹果和国光苹果这两种苹果耐贮存差异不显著习题5.71、数据输入variable view定义变量（品种，植株，株数），Date view（数据输入）2、统计分析Dateweight case by：frequency variable：株数okAnalyzedescriptive statisticscrosstable：row：品种，columu：植株状况statistics chi-squarecontiueok3、结果分析Chi-Square TestsValuedfAsymp. Sig. (2-sided)Pearson Chi-Square5.622a4.229Likelihood Ratio5.5354.237N of Valid Cases547a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 8.78. 结论：df=4，n=547，x2=5.622，p=0.229大于0.05，接受Ho，叶片衰老与灌溉方式无关第四次上机：统计推断 方差同质检验 非参数检验实验目的：理解方差同质性检验的目的与方法，熟悉非参数检验方法实验步骤及结果分析习题6.41、数据输入variable view定义变量（氯化钠溶液处理浓度 ，分组，芽长），Date view（数据输入）2、统计分析Analyzecompare meansone-way ANOVA dependent：芽长，factor ：氯化钠溶液处理浓度option：descripve homogeneity of variable testcontinuepost hoc：lsd snk Duncanok3、结果分析ANOVA芽长Sum of SquaresdfMean SquareFSig.Between Groups22.60937.53615.225.001Within Groups3.9608.495Total26.56911F=15.225，表明4种不同浓度的氯化钠溶液处理种子的发芽情况呈极显著差异芽长习题6.4NSubset for alpha = 0.0512Student-Newman-Keulsa10035.1335036.2001037.867038.633Sig.100.219Duncana10035.1335036.2001037.867038.633Sig.100.219Means for groups in homogeneous subsets are displayed.a. Uses Harmonic Mean Sample Size = 3.000.通过s-n-k法比较4浓度之间对种子处理发芽情况的差异：100ug/g与50ug/之间的差异不显著，100ug/g与10ug/g和0ug/g之间呈显著差异，50ug/g与10ug/g之间差异不显著 ，通过srr法比较4种浓度对种子发芽情况的影响的差异与s-n-k法得出的结论相同gMultiple ComparisonsDependent Variable:芽长(I) 习题6.4(J) 习题6.4Mean Difference (I-J)Std. ErrorSig.95% Confidence IntervalLower BoundUpper BoundLSD010.7667.5745.219-.5582.091502.4333*.5745.0031.1093.7581003.5000*.5745.0002.1754.825100-.7667.5745.219-2.091.558501.6667*.5745.020.3422.9911002.7333*.5745.0011.4094.058500-2.4333*.5745.003-3.758-1.10910-1.6667*.5745.020-2.991-.3421001.0667.5745.100-.2582.3911000-3.5000*.5745.000-4.825-2.17510-2.7333*.5745.001-4.058-1.40950-1.0667.5745.100-2.391.258Dunnett t (2-sided)a100-.7667.5745.446-2.421.888500-2.4333*.5745.007-4.088-.7791000-3.5000*.5745.001-5.154-1.846*. The mean difference is significant at the 0.05 level.a. Dunnett t-tests treat one group as a control, and compare all other groups against it.通过lsd法得p(sig)0.05,差异不显著，p0.05差异显著，p0.01差异极显著，故由此可得出不同浓度处理发芽间的差异：0ug/g与10ug/g之间差异不显著，0ug/g与50ug/g和100ug/g之间呈极显著差异，10ug/g与50ug/g呈显著差异，10ug/g与100ug/g呈极显著差异，50ug/g与100ug/g之间差异不显著习题6.51、数据输入variable view定义变量（母猪品种和仔猪断奶时体重），Date view（数据输入）2、统计分析Analyzecompare meansone-way ANOVA dependent：仔猪断奶时体重，factor ：母猪品种option：descripve homogeneity of variable testcontinuepost hoc：lsd snk Duncanok3、结果分析ANOVA体重Sum of SquaresdfMean SquareFSig.Between Groups153.530276.76521.515.000Within Groups74.929213.568Total228.45823由表F=21.515 母猪对仔猪体重效应的差异极显著Multiple ComparisonsDependent Variable:体重(I) 习题6.5(J) 习题6.5Mean Difference (I-J)Std. ErrorSig.95% Confidence IntervalLower BoundUpper BoundLSD122.7143*.9776.011.6814.74736.0000*.9179.0004.0917.90921-2.7143*.9776.011-4.747-.68133.2857*.9519.0021.3065.26531-6.0000*.9179.000-7.909-4.0912-3.2857*.9519.002-5.265-1.306Dunnett t (2-sided)a21-2.7143*.9776.021-5.032-.39731-6.0000*.9179.000-8.176-3.824*. The mean difference is significant at the 0.05 level.a. Dunnett t-tests treat one group as a control, and compare all other groups against it.通过lsd法比较不同种母猪与同一公猪交配所产仔猪断奶时体重之间的差异1与2之间差异呈显著，2与3之间呈极显著差异，1与3之间呈极显著差异体重习题6.5NSubset for alpha = 0.05123Student-Newman-Keulsa3916.5002719.7861822.500Sig.1.0001.0001.000Duncana3916.5002719.7861822.500Sig.1.0001.0001.000Means for groups in homogeneous subsets are displayed.a. Uses Harmonic Mean Sample Size = 7.916.通过s-n-k法比较不同种母猪对仔猪体重效应的差异显著性，1与2呈显著差异，2与3呈显著差异，1与3呈显著差异习题6.61、数据输入variable view定义变量（品种，室温 ，每100mg血液中葡萄糖含量），Date view（数据输入）2、统计分析Analyzegeneral linear modelunivariable：dependenvariablet：每100mg血液中葡萄糖含量，fixed factor：品种 ，室温continueoption：descripve statisticscontinuepost hoc：lsd snk Duncanok3、结果分析习题6.6Tests of Between-Subjects EffectsDependent Variable:血糖值SourceType I Sum of SquaresdfMean SquareFSig.Corrected Model13288.607a91476.51216.084.000Intercept373296.0361373296.0364066.511.000品种2758.3933919.46410.016.000室温10530.21461755.03619.119.000Error1652.3571891.798Total388237.00028Corrected Total14940.96427a. R Squared = .889 (Adjusted R Squared = .834)有方差分析得F=10.02，各种家兔血糖值之间呈极显著差异，室温间F=19.12，室温对家兔的影响极显著差异血糖值习题6.6NSubset123Student-Newman-Keulsa7102.297110.57110.577120.43120.437128.57Sig.123.070.129Duncana7102.297110.57110.577120.43120.437128.57Sig.123.070.129Means for groups in homogeneous subsets are displayed. Based on observed means. The error term is Mean Square(Error) = 91.798.a. Uses Harmonic Mean Sample Size = 7.000.品种与之间差异不显著, 与之间差异不显著, 与之间差异不显著, 与之间差异显著, 与、之间差异显著血糖值室温NSubset1234Student-Newman-Keulsa20489.2515491.50254107.50104120.00120.00304122.50122.5054130.00354147.50Sig.744.096.3251.000Duncana20489.2515491.50254107.50104120.00120.00304122.5054130.00354147.50Sig.744.082.1791.000Means for groups in homogeneous subsets are displayed. Based on observed means. The error term is Mean Square(Error) = 91.798.a. Uses Harmonic Mean Sample Size = 4.000.通过s-n-k比较不同室温对家兔血糖值得影响之间的差异显著性20与15之间差异不显著，25与30之间差异不显著，30与5之间差异不显著，25与10之间差异不显著，30与10之间差异不显著，10与5之间差异不显著，20与25、10、30、5、35之间差异显著，15与25、10、30、5、35之间差异显著，25与20、15、5、35之间差异显著，10与20、15、5、35之间差异显著，30与20、15、35之间差异显著，5与20、15、25、10、5、30之间差异显著习题6.71、数据输入variable view定义变量（原料，温度，生长情况），Date view（数据输入）2、统计分析Analyzegeneral linear modelunivariable：dependenvariablet：生长情况，fixed factor：原料，温度 ，室温continueoption：descripve statisticscontinuepost hoc：lsd snk Duncanok3、结果分析Tests of Between-Subjects EffectsDependent Variable:结果SourceType III Sum of SquaresdfMean SquareFSig.Corrected Model5513.500a8689.18811.233.000Intercept37636.000137636.000613.445.000原料1554.1672777.08312.666.000温度3150.50021575.25025.676.000原料 * 温度808.8334202.2083.296.025Error1656.5002761.352Total44806.00036Corrected Total7170.00035a. R Squared = .769 (Adjusted R Squared = .701)结果习题6.NSubset12Student-Newman-KeulsaA11223.58A21234.00A31239.42Sig.1.000.102DuncanaA11223.58A21234.00A31239.42Sig.1.000.102Means for groups in homogeneous subsets are displayed. Based on observed means. The error term is Mean Square(Error) = 61.352.a. Uses Harmonic Mean Sample Size = 12.000.通过s-n-k法比较不同原料对物质生长影响之间的差异显著性：A1与A2之间差异显著，A1与A3之间差异显著，A2与A3之间差异不显著结果温度NSubset123Student-Newman-Keulsa401220.17351233.92301242.92Sig.1.0001.0001.000Duncana401220.17351233.92301242.92Sig.1.0001.0001.000Means for groups in homogeneous subsets are displayed. Based on observed means. The error term is Mean Square(Error) = 61.352.a. Uses Harmonic Mean Sample Size = 12.000.通过s-n-k法比较不同温度对物质生长影响之间的差异显著性：B3与B2之间差异显著，B2与B1之间差异显著，B3与B1之间差异显著第五次上机 直线回归与相关分析实验目的;理解线性回归与相关分析得基本原理，熟悉使用spass实现线性回归相关的统计方法实验步骤及分析结果习题7、4-1、数据输入variable view定义变量（4月下旬平均气温x，5月上旬50株棉蚜虫数y），Date view（数据输入）2、统计分析Analyzeregressionlinear-dependent：5月上旬50株棉蚜虫数y，independent：4月下旬平均气温xstatistics：descriptivescontinueok3、结果分析CoefficientsaModelUnstandardized CoefficientsStandardized CoefficientstSig.BStd. ErrorBeta1(Constant)-283.68063.872-4.441.001四月下旬平均气温x18.0843.387.8605.339.000a. Dependent Variable: 五月上旬50株棉蚜虫数ya=18.084，b=-283.680，y=18.084x-283.680ANOVAbModelSum of SquaresdfMean SquareFSig.1Regression55.842155.84228.510.000aResidual19.587101.959Total75.42911a. Predictors: (Constant), 五月上旬50株棉蚜虫数yb. Dependent Variable: 四月下旬平均气温xF=28.510.所以否定H0，接受HA，说明五月上旬50株棉蚜虫数与四月下旬平均气温之间有极显著的直线回归关系习题7.51、数据输入variable view定义变量（进食量，增重量，小数位数都定义为0），Date view（数据输入）2、统计分析Analyzeregressionlinear-dependent：增重量，independent：进食量statistics：descriptivescontinueok3、结果分析CoefficientsaModelUnstandardized CoefficientsStandardized CoefficientstSig.BStd. ErrorBeta1(Constant)-47.35351.605-.918.394进食量.261.065.8544.018.007a. Dependent Variable: 增重量CoefficientsaModel95% Confidence Interval for BLower BoundUpper Bound1(Constant)-173.62778.921进食量.102.420a. Dependent Variable: 增重量a=0.261，b=-47.353，y=0.261x-47.353，回归系数的95%置信区间为（0.102,0.420）相关系数为0.854，t值为4.018，p=0.0070,.01即线性回归系数为0.261，是极显著，表明增重量与进食量存在极显著的线性关系协方差分析习题10.21、数据输入variable view定义变量（肥料，梨树的起始干周x，梨树的单株产量y），Date view（数据输入）2、统计分析Analyzegeneral linear modelunivariable：dependenvariablet：梨树的单株产量y，fixed factor：肥料，covariate：梨树的起始干周xcontinueoption：descripve statisticsdisply means for ：肥料compare main effectcontinueok3、结果分析Tests of Between-Subjects EffectsDependent Variable:单珠产量SourceType III Sum of SquaresdfMean SquareFSig.Corrected Model3086.893a4771.72318.312.000Intercept3280.47413280.47477.841.000肥料2507.7773835.92619.835.000梨树的起始干周475.9931475.99311.295.002Error1475.0073542.143Total168658.00040Corrected Total4561.90039a. R Squared = .677 (Adjusted R Squared = .640)F=19.835，说明肥料对梨树单株产量的影响差异达到显著水平Pairwise ComparisonsDependent Variable:单珠产量(I) 习题10.2(J) 习题10.2Mean Difference (I-J)Std. ErrorSig.a95% Confidence Interval for DifferenceaLower BoundUpper BoundA1A26.849*2.927.025.90712.791A315.670*2.919.0009.74321.596A420.558*2.906.00014.65926.458A2A1-6.849*2.927.025-12.791-.907A38.821*2.904.0042.92514.716A413.710*2.913.0007.79519.624A3A1-15.670*2.919.000-21.596-9.743A2-8.821*2.904.004-14.716-2.925A44.8892.908.102-1.01610.793A4A1-20.558*2.906.000-26.458-14.659A2-13.710*2.913.000-19.624-7.795A3-4.8892.908.102-10.7931.016Based on estimated marginal means*. The mean difference is significant at the .05 level.a. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).各肥料的校正，梨树的单株产量y的比较结果表明，肥料A与A2之间其校正梨树单株产量平均值间存在显著差异，与A3,、A4间存在极显著差异，A2与A3、A4之间其校正梨树单株产量平均值间存在极显著差异，A3与A4间无显著差异EstimatesDependent Variable:单珠产量习题10.2MeanStd. Error95% Confidenc