实验设计与数据处理第三四五章例题及课后习题答案

于是 三元线性回归方程为：y=0.197+0.0455x1-0

（1）F检验例4-6

试验号

1

2

3

4

5

6

7

8

SUM

AVE反应温度x1/℃反应时间x2/h反应物含量x3/%得率y701017.67010310.3703018.97030311.2901018.49010311.1903019.89030312.66401601679.9802029.9875

SUMMARY OUTPUT

回归统计

Multiple R0.99645389

R Square0.992920354

Adjusted R 0.987610619

标准误差

观测值方差分析0.1837117318

df回归分析残差

总计347SS18.933750.13519.06875

标准误差

0.554949322

0.006495191

0.006495191

0.064951905MS6.311250.03375F187

CoefficientsIntercept2.1875X Variable 0.04875X Variable 0.06375X Variable 1.3125t Stat3.9418013747.5055534999.81495457620.20725942P-value0.0169340.0016860.0006043.54E-05

所以得到的线性回归方程表达式为：y=2.1875+0.04875x1+0.06375x2+1.3125x3

例4-7

p/atm

M/(mol/min)2.010.7631.780.7151.750.711.730.695

1

2

3

4

5

6

7

8

9

10

SUMp/atm2.011.781.751.731.681.621.41.360.930.5314.79M/(mol/min)0.7630.7150.710.6950.6980.6730.630.6120.4980.3716.365xy2xilg(pi)lg(Mi)0.303196057-0.1174754620.0919280.250420002-0.1456939580.062710.243038049-0.1487416510.0590670.238046103-0.1580151950.0566660.225309282-0.1561445770.0507640.209515015-0.1719849360.0438970.146128036-0.2006594510.0213530.133538908-0.2132485780.017833-0.031517051-0.3027706570.000993-0.27572413-0.430626090.0760241.44195027-2.0453605560.481235

AVE1.479

SUMMARY OUTPUT0.63650.144195027-0.204536056

回归统计

Multiple R0.999492866R Square0.998985989

Adjusted R 0.998859237标准误差0.00319584

观测值10方差分析

df

回归分析

残差

总计189SS0.0804964268.17071E-050.080578133

标准误差

0.001341014

0.006113002F

0.01(1,8)=11.3MSF0.0804964267881.4591.02134E-05CoefficientsIntercept-0.282790341X Variable 0.542697532t StatP-value-210.8779792.86E-1688.777581472.89E-13

例4-8

xi

yi

i

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2

3

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5

6

7

8

9

SUM

AVExi1345678910535.888889yi2781011121098778.55555555612x11345678910535.88888888937x248y1297168251036114912641081910083817742.333333338.555556510

回归统计

Multiple R0.981636002

R Square0.96360924

Adjusted R 0.951478987

标准误差0.643254553

观测值9

方差分析

df

回归分析

残差

总计268F0.01(2,6)=10.92SS65.73956372.48265851868.22222222

标准误差

0.846062418

0.330019174

0.028576121MSF32.8697818579.438510.41377642CoefficientsIntercept-1.715966387X Variable 3.750076394X Variable -0.279029794t Stat-2.02817942211.36320764-9.764439272P-value0.0888882.78E-056.63E-05

例4-9

i

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2

3

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5

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7

sumx111.41.82.22.633.415.4x213192510162228133x31.5312.50.523.514y0.330.3360.2940.4760.2090.4510.4822.578

SUMMARY OUTPUT回归统计

Multiple R0.983812569R Square0.967887171

Adjusted R 0.935774341标准误差0.026331591

观测值7方差分析df回归分析残差

总计336SS0.0626933710.0020800580.064773429

标准误差

0.042352824

0.047467569

0.012883654

0.005824205F0.05(3,3)=9.28MSF0.0208977930.14020.000693353CoefficientsIntercept0.057886497X Variable 0.252172538X Variable -0.064840835X Variable 0.028317025t Stat1.366768285.312522719-5.0327985034.861955457P-value0.2651140.0130250.0151190.016617

习题3.1

颜色

橘黄色

粉色

绿色

无色销售额/万元25.130.828.532.426.531.227.930.828.728.325.129.629.127.924.231.7

方差分析：单因素方差分析

SUMMARY

组

行 1

行 2

行 3

行 4观测数5555求和136.6147.8132.2157.3平均27.3229.5626.4431.46方差2.6722.1433.2981.658

方差分析

差异源

组间

组内SS76.845539.084df316MS25.615166672.44275F10.4862

总计115.929519习题3.2乙炔流量/（L/min）

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1.5

2

2.5空气流量/（L/min）91081.580.381.879.476.175.467.968.7881.181.47560.4118079.175.469.8

方差分析：无重复双因素分析

SUMMARY

行 1

行 2

行 3

行 4

列 1

列 2

列 3

列 4

列 5观测数555544444求和399.9397.6372.7335.5297.9307.3303.8304.3292.4平均79.9879.5274.5467.1方差3.1375.5074.52814.48574.47596.742576.82542.262575.9527.8966776.07521.462573.115.9

方差分析

差异源

行

列

误差

总计SS537.637535.47375.155648.2655df341219MSF179.212528.614868.868251.4159946.262916667

习题3.3

铝材材质去离子水

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1

2

2自来水2.31.81.51.55.65.35.34.8

3

31.82.37.47.4

方差分析：可重复双因素分析

SUMMARY

1观测数求和平均

方差

2

观测数

求和

平均

方差

3

观测数

求和

平均

方差

总计

观测数

求和

平均

方差24.12.050.125214.87.40418.94.7259.5825231.50210.15.050.125413.13.2754.242524.12.050.125210.95.450.0454153.753.91去离子水自来水总计611.21.8666666670.130666667635.85.9666666671.298666667

方差分析

差异源

样本

列

交互

内部

总计SS4.37166666750.432.3550.4257.57666667df212611MSF2.18583333331.2261950.43720.42861.177516.821430.07

习题4.1

c/%(x)T/℃（y)

19.6105.4

20.5106

22.3

25.1

26.3

27.8

29.1107.2108.9109.6110.7111.5

i

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7

总和

平均x19.620.522.325.126.327.829.1170.724.38571y105.4106107.2108.9109.6110.7111.5759.3108.4714286xi2384.16420.25497.29630.01691.69772.84846.814243.05yi211109.161123611491.8411859.2112012.1612254.4912432.2582395.11xiyi2065.8421732390.562733.392882.483077.463244.6518567.38

SUMMARY OUTPUT

回归统计

Multiple R0.999752712

R Square0.999505486

Adjusted R 0.999406583

标准误差0.056916528观测值7

方差分析df

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