卫生统计学卫生统计学 (31).docx

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1、单选题1 相关系数检验的备择假设F是（）A.p0B.p=OC. p=lD/邦2 .由样本计算两个随机变量和y之间的简单相关系数的值近似等于零，经统计检验得到尸=0.90。作 结论时，正确的表述应该是（）a.x与y之间呈直线关系b.x与丫之间呈曲线关系c.x与y之间不存在直线相关关系d.x与y之间无关联3 .线性回归分析的原理是对因变量Y的总体变异进行分解。它可能出现（）A. SS .斫SS回B. SS总,SS剩C. SS fSS回D.以上都有可能4 .对变量x和y同时进行简单相关分析和简单回归分析，其结果有（）A. r 0, Z? 0B. r 0C. r 0, b 0D. r= b5 .已知r

2、=l,则一定有（）A. b = 1B. a = 1C. SS 剩=0D. SS 总二 SS 剩6 .含有常数项的直线回归系数假设检验，其自由度是（）A. nB.n-1C. n-2D. 2n-l7 .适合分析糖尿病人的血糖水平与胰岛素水平之间关系的方法是（）A.配对比较的“佥验8 .成组比较的才检验C.相关分析或回归分析D./2检验8.对简单线性回归模型进行显著性检验的目的是推断（）。A.样本斜率B.总体斜率Correlations身高体重身高 Pearson Correlation1.866Sig. (2-tailed),000N1312体重 Pearson Correlation.8661S

3、ig. (2-tailed).000N1212*. Correlation is significant at the 0.01 level (2-tailed).Model SummaryModelRR SquareAdjusted R SquareStd. Error of the Estimate1.866a.750.7252.460a. Predictors: (Constant),身高ANOVAaModelSum of SquaresdfMean SquareFSig.1Regression181.7481181.74830,040,000bResidual60.502106.050

4、Total242.25011a. DependentVariable:体Db. Predictors: (Constant),身高Coefficients3ModelUnstandardized CoefficientsStandardizedCoefficientstSig.BStd. ErrorBeta1(Constant)身高-5.564.2405.848.044.866-.9515.481,364.000a. DependentVariable:体季下列说法错误的是（）A.上述资料中身高数据服从正态分布B.上述资料中体重数据服从正态分布C.可以采用pearson积差相关系数描述身高和体

5、重资料的相关性D. pearson积差相关系数需采用方差分析的方法进行非零判断填空题4 .某研究机构随机抽取12名营养缺乏的儿童，测量身高（cm）与体重（kg）,数据如表1所示。SPSS 分析结果如下：表1 12名营养缺乏儿童的身高与体重10编号身甑cm体重kg114327214830312323415528512723612524713733812125910519101072011153331214430Tests of NormalityoOooOo oo0o oO11ITI-T10011012013014015016030-20-15-身高Kolmogorov-Smirnov3Shap

6、iro-WilkStatisticdfSig.StatisticdfSig.身高.15312.200,93812,470体重.12112,200s.95012.64035-11Correlations身高体重身高 Pearson Correlation1.866Sig. (2-tailed),000N1312体重 Pearson Correlation.8661Sig. (2-tailed).000N1212*. Correlation is significant at the 0.01 level (2-tailed).Model SummaryModelRR SquareAdjusted

7、 R SquareStd. Error of the Estimate1.866a.750.7252.460a. Predictors: (Constant),身高ANOVAaModelSum of SquaresdfMean SquareFSig.1Regression181.7481181.74830,040,000bResidual60.502106.050Total242.25011a. DependentVariable:体Db. Predictors: (Constant),身高Coefficients3ModelUnstandardized CoefficientsStandar

8、dizedCoefficientstSig.BStd. ErrorBeta1(Constant)身高-5.564.2405.848.044.866-.9515.481,364.000a. DependentVariable:体季身高和体重的相关系数是,该值()统计学意义。判断题5 .某研究机构随机抽取12名营养缺乏的儿童，测量身高(cm)与体重(kg),数据如表1所示。SPSS 分析结果如下：表1 12名营养缺乏儿童的身高与体重12编号身甑cm体重kg114327214830312323415528512723612524713733812125910519101072011153331214

9、430Tests of NormalityoOooOo oo0o oO11ITI-T10011012013014015016030-20-15-身高Kolmogorov-Smirnov3Shapiro-WilkStatisticdfSig.StatisticdfSig.身高.15312.200,93812,470体重.12112,200s.95012.64035-13Correlations身高体重身高 Pearson Correlation1.866Sig. (2-tailed),000N1312体重 Pearson Correlation.8661Sig. (2-tailed).000N1

10、212*. Correlation is significant at the 0.01 level (2-tailed).Model SummaryModelRR SquareAdjusted R SquareStd. Error of the Estimate1.866a.750.7252.460a. Predictors: (Constant),身高ANOVAaModelSum of SquaresdfMean SquareFSig.1Regression181.7481181.74830,040,000bResidual60.502106.050Total242.25011a. Dep

11、endentVariable:体Db. Predictors: (Constant),身高Coefficients3ModelUnstandardized CoefficientsStandardizedCoefficientstSig.BStd. ErrorBeta1(Constant)身高-5.564.2405.848.044.866-.9515.481,364.000a. DependentVariable:体季身高和体重资料相关性较弱。()单选题6 .某研究机构随机抽取12名营养缺乏的儿童，测量身高(cm)与体重(kg),数据如表1所示。SPSS 分析结果如下：表1 12名营养缺乏儿童

12、的身高与体重14编号身甑cm体重kg114327214830312323415528512723612524713733812125910519101072011153331214430Tests of NormalityoOooOo oo0o oO11ITI-T10011012013014015016030-20-15-身高Kolmogorov-Smirnov3Shapiro-WilkStatisticdfSig.StatisticdfSig.身高.15312.200,93812,470体重.12112,200s.95012.64035-15Correlations身高体重身高 Pearso

13、n Correlation1.866Sig. (2-tailed),000N1312体重 Pearson Correlation.8661Sig. (2-tailed).000N1212*. Correlation is significant at the 0.01 level (2-tailed).Model SummaryModelRR SquareAdjusted R SquareStd. Error of the Estimate1.866a.750.7252.460a. Predictors: (Constant),身高ANOVAaModelSum of SquaresdfMean

14、 SquareFSig.1Regression181.7481181.74830,040,000bResidual60.502106.050Total242.25011a. DependentVariable:体Db. Predictors: (Constant),身高Coefficients3ModelUnstandardized CoefficientsStandardizedCoefficientstSig.BStd. ErrorBeta1(Constant)身高-5.564.2405.848.044.866-.9515.481,364.000a. DependentVariable:体

15、季欲采用假设检验的方法对身高和体重的相关系数进行非零统计检验，其原假设是()A.p=0B.R0C.r=0D.#0单选题7 .某研究机构随机抽取12名营养缺乏的儿童，测量身高(cm)与体重(kg),数据如表1所示。SPSS 分析结果如下：表1 12名营养缺乏儿童的身高与体重16编号身甑cm体重kg114327214830312323415528512723612524713733812125910519101072011153331214430Tests of NormalityoOooOo oo0o oO11ITI-T10011012013014015016030-20-15-身高Kolmog

16、orov-Smirnov3Shapiro-WilkStatisticdfSig.StatisticdfSig.身高.15312.200,93812,470体重.12112,200s.95012.64035-17Correlations身高体重身高 Pearson Correlation1.866Sig. (2-tailed),000N1312体重 Pearson Correlation.8661Sig. (2-tailed).000N1212*. Correlation is significant at the 0.01 level (2-tailed).Model SummaryModel

17、RR SquareAdjusted R SquareStd. Error of the Estimate1.866a.750.7252.460a. Predictors: (Constant),身高ANOVAaModelSum of SquaresdfMean SquareFSig.1Regression181.7481181.74830,040,000bResidual60.502106.050Total242.25011a. DependentVariable:体Db. Predictors: (Constant),身高Coefficients3ModelUnstandardized Co

18、efficientsStandardizedCoefficientstSig.BStd. ErrorBeta1(Constant)身高-5.564.2405.848.044.866-.9515.481,364.000a. DependentVariable:体季欲采用假设检验的方法对回归系数进行非零统计检验，其备择假设是() 羯邛二08 .四0C. b=QD.厚0填空题8 .某研究机构随机抽取12名营养缺乏的儿童，测量身高(cm)与体重(kg),数据如表1所示。SPSS 分析结果如下：表112名营养缺乏儿童的身高与体重18编号身甑cm体重kg11432721483031232341552851

19、2723612524713733812125910519101072011153331214430Tests of NormalityoOooOo oo0o oO11ITI-T10011012013014015016030-20-15-身高Kolmogorov-Smirnov3Shapiro-WilkStatisticdfSig.StatisticdfSig.身高.15312.200,93812,470体重.12112,200s.95012.64035-19C.样本均数D.总体均数9 .如果对简单线性回归模型进行显著性检验的结果是不能拒绝”o,这就意味着（）A.该模型有应用价值10 该模型无应

20、用价值C.该模型求错了d.x与y之间毫无关系10 .对两个数值变量同时进行了相关和回归分析，厂有统计学意义（P 加血糖。 (stoILA 衣1/531.90P4.53311.273.731.647.32P6.38.832633.536%10.812.3- d4版1.07P5叱8.311.6*5小432.32*4.057913*6.050.W1缶13介1S3Q74.908.5OP23S&11.1PS-7.0a3.00P6.7511.512.293.8532.1W16.2 肝7.99.3p104.6530.636.57.WS.4 一d4.5N1.9拄3.6W9.3 一12-4*1.9W6.617.

21、810介Model SummaryModelRR SquareAdjusted R SquareStd. Error of theEstimate1. 7倍.601.5282.0095.a. Predictors: (Constant), x4, x2, x3, x1ANOVAbModelSum of SquaresdfMean SquareFSig.1Regression133.711433.4288.278.000aResidual88.841224.038Total222.55226a. Predictors: (Constant), x4, x2, x3, x1b. Dependent

22、 Variable: yCoefficients3ModelUnstandardizedCoefficientsStandardizedCoefficientstSig.CollinearityStatisticsBStd. ErrorBetaToleranceVIF1(Constant)5.9432.8292.101.047x1.142.366.078.390.021.4582.186x2.351.204.3091.721.009.5621.780x3-.271.121-.339-2.229.036.7821.278x4.638.243.3982.623.016.7891.267a. Dep

23、endent Variable: y下列说法正确的是()A.该资料采用多重线性回归方法进行分析B.需采用方差分析的方法对回归模型进行统计检验25C.该回归模型的决定系数为0.775D.四个因素都是血糖的影响因素E.四个因素当中，糖化血红蛋白对血糖的影响最大填空题2. 27名糖尿病患者的血清总胆固醇、甘油三酯、空腹胰岛素、糖化血红蛋白、空腹血糖的测量值列于表1,分析如下：表1 27名糖尿病患者的血糖及有关变量的测量结果序号d 妒总胆固醇酶以L*如甘油三酉2 (21LA xg胰岛素延向A猊糖化血红蛋白一 (%A 加血糖” 1/531.90P4.53311.2Q*2d3.731.647.32P6.X

24、S.M3r633.536%10.812.3-4版1.07P5叱如11.6P*43232d4.057.513.4*6.050.641缶13介1S.3-3及4.908.5OP238.511.1 8P7.0a3.00P6.7511.512g93.8532.1W1628P7.996p104.653036.5小8.4124.5N1.97P3.6W9.3312-4*1.976.617.810介26Model SummaryModelRR SquareAdjusted R SquareStd. Error of theEstimate1.775a.601.5282.0095.a. Predictors: (

25、Constant), x4, x2, x3, x1ANOVAbModelSum of SquaresdfMean SquareFSig.1Regression133.711433.4288.278.000aResidual88.841224.038Total222.55226a. Predictors: (Constant), x4, x2, x3, x1 b. Dependent Variable: yCoefficients3ModelUnstandardizedCoefficientsStandardizedCoefficientstSig.CollinearityStatisticsB

26、Std. ErrorBetaToleranceVIF1(Constant)5.9432.8292.101.047x1.142.366.078.390.021.4582.186x2.351.204.3091.721.009.5621.780x3-.271.121-.339-2.229.036.7821.278x4.638.243.3982.623.016.7891.267a. Dependent Variable: y根据分析模型，总胆固醇、甘油三酯、胰岛素、糖化血红蛋白的偏回归系数分别是、 、和o判断题3. 27名糖尿病患者的血清总胆固醇、甘油三酯、空腹胰岛素、糖化血红蛋白、空腹血糖的测量值列于表, 分析如下：表1