工程数学课后10答案.doc

工程数学（张有方等编浙大出版）课后答案第10章 方差分析与回归分析1、拉罐玻璃瓶塑料袋304218404826183840243636方差分析：单因素方差分析SUMMARY组观测数求和平均方差列 141122888列 241644128列 341203098.66666667方差分析差异源SSdfMSFP-valueF crit组间39221962.7391304350.1177254.256494729组内644971.55556总计1036112.7391304350.05接受2、123454.36.16.59.39.57.87.38.38.78.83.24.28.67.211.46.54.18.210.17.8方差分析：单因素方差分析SUMMARY组观测数求和平均方差列 1421.85.454.336666667列 2421.75.4252.409166667列 3431.67.90.9列 4435.38.8251.5025列 5437.59.3752.309166667方差分析差异源SSdfMSFP-valueF crit组间55.537413.884256.0590224740.0041574.893209589组内34.3725152.2915总计89.9095196.0590224744.893209589拒绝 0.0041570.01拒绝3、810111292211510121913417方差分析：无重复双因素分析SUMMARY观测数求和平均方差行 14481251.33333333行 245313.2544.25列 124120.54.5列 2224122列 3294.50.5列 422713.524.5方差分析差异源SSdfMSFP-valueF crit行3.12513.1250.3303964760.60575.538319455列258.375386.1259.1057268720.0512475.39077328误差28.37539.458333总计289.87570.3303964760.1接受9.1057268725.39077328拒绝 0.0512475.987377584拒绝 0.0266325.14325285拒绝 0.0001680.05拒绝1.9736842110.05接受5、密度百分比浓度1.0111.07101.14201.22301.3401.4501.5601.61701.73801.81901.8498SUMMARY OUTPUT回归统计Multiple R0.996865R Square0.993739Adjusted R Square0.993044标准误差2.728839观测值11方差分析dfSSMSFSignificance F回归分析110637.8900110637.890011428.5633.15E-11残差967.019082027.446564669总计1010704.90909Coefficients标准误差t StatP-valueLower 95%Upper 95%Intercept-105.3594.18959986-25.147710421.19E-09-114.836-95.88131075X Variable 1109.27372.89111734437.796341573.15E-11102.7335115.8138204即列 1列 2列 11列 20.99686516、时间深度561082012301540175020602580291003512042SUMMARY OUTPUT回归统计Multiple R0.997993R Square0.995989Adjusted R Square0.995488标准误差0.790024观测值10方差分析dfSSMSFSignificance F回归分析11239.9069021239.9069021986.5937.09E-11残差84.9930983030.624137288总计91244.9Coefficients标准误差t StatP-valueLower 95%Upper 95%Intercept5.2357770.43119093212.142595121.96E-064.2414496.230104979X Variable 10.304160.00682412844.57121517.09E-110.2884230.319896139即7、年龄千人死亡率对数化102.10.741937203.61.280934304.11.410987406.81.9169235011.22.4159146024.43.1945837060.64.104295SUMMARY OUTPUT回归统计Multiple R0.977510184R Square0.95552616Adjusted R Square0.946631393标准误差0.272029118观测值7方差分析dfSSMSFSignificance F回归分析17.9494804827.94948107.42560.000143935残差50.3699992050.074总计68.319479687Coefficients标准误差t StatP-valueLower 95%Upper 95%Intercept0.0208963650.2299065660.0908910.931108-0.5700972780.61189X Variable 10.0532832070.00514086710.364630.0001440.0400681880.066498即？a=1.021116223b=0.053283207？8、标准温度测定温度33324645.555566160.37576.18382.29292.410099.3115110.4121114.3138125.4156135.8173145.3200158.8SUMMARY OUTPUT回归统计Multiple R0.999357R Square0.998715Adjusted R Square0.998501标准误差0.902236观测值8方差分析dfSSMSFSignificance F回归分析13795.9908183795.9908184663.2066.63E-10残差64.8841816240.814030271总计73800.875Coefficients标准误差t StatP-valueLower 95