4全國(guó)高技術(shù)產(chǎn)業(yè)主營(yíng)業(yè)務(wù)收入影響因素逐步回歸分析報(bào)告模版

1、、原始數(shù)據(jù)全國(guó)高技術(shù)產(chǎn)業(yè)基本情況年份主宮業(yè)務(wù)收入 （億元）出口交貨值 （億元）R&機(jī)構(gòu)數(shù)R&經(jīng)費(fèi)（億元）專利申請(qǐng)數(shù)新產(chǎn)品開發(fā)經(jīng)費(fèi) （億元）施工項(xiàng)目數(shù)固定資產(chǎn)投資額 （億元）1995P 3,917.401,125.202,138.0018.00612.0032.5019964,497.001,890.0030.96545.0041.292,507.00306.6019975,618.001,680.0042.02713.0052.642,677.00336.751998P 6,580.002,041.811,735.0056.451,076.0070.842,371.00391.8819997,

2、820.002,413.021,809.0067.561,482.0094.432,685.00408.52200010,034.003,388.401,379.00114.002,245.00118.002,738.00568.00200112,015.004,281.971,372.00157.013,379.00134.543,377.00739.762002P 14,614.256,020.021,374.00186.975,590.00169.014,165.00986.78200320,411.529,098.271,259.00222.458,270.00207.596,436.

3、001,423.13200427,846.2014,830.901,732.00292.1311,026.00258.826,334.001,790.492005P 33,921.8017,636.001,619.00362.5016,823.00415.707,095.002,144.00-200641,584.5623,476.461,929.00456.4424,301.00509.957,507.002,761.02200749,714.1028,422.802,217.00545.3234,446.00652.037,789.003,388.352008P 55,728.9031,5

4、03.902,534.00655.2039,656.00798.408,534.004,169.20200959,566.7029,499.702,845.00774.0051,989.00925.1010,201.005,241.90201074,482.8037,001.603,184.00967.8059,683.001,006.9010,723.006,944.70201187,527.2040,600.333,254.001,237.8077,725.001,528.0013,204.009,468.462012102,284.0046,701.104,566.001,491.499

5、7,200.001,827.4815,681.0012,932.702013116,048.9049,285.104,583.001,734.40102,532.002,069.5017,691.0015,557.702014127,367.7050,765.204,763.001,922.20120,077.002,350.6018,403.0017,451.702015P 139,968.6550,923.135,572.002,219.70114,562.002,574.6020,028.0019,950.65-2016153,796.3352,444.616,456.002,437.6

6、1131,680.003,000.3623,715.0022,786.70數(shù)據(jù)來源：Wind二、變量設(shè)定建立高技術(shù)產(chǎn)業(yè)主營(yíng)收入的逐步回歸模型， 說明逐步回歸分析的具體 步驟。影響高技術(shù)產(chǎn)業(yè)主營(yíng)收入的因子一共有 7個(gè)，通過逐步回歸，從中 選出對(duì)高技術(shù)產(chǎn)業(yè)主營(yíng)收入影響顯著的因子，從而建立相應(yīng)的模型。變量說明如下：y：主營(yíng)業(yè)務(wù)收入莖1：出口交貨值V V2： R&D機(jī)構(gòu)數(shù)3： R&D經(jīng)費(fèi)V vS專利申請(qǐng)數(shù)，新產(chǎn)品開發(fā)經(jīng)費(fèi)6施工項(xiàng)目數(shù)7：固定資產(chǎn)投資額三、利用SPSS22逐步回歸（步驟略）四、逐步回歸結(jié)果分析主要結(jié)果：表i變量已輸入/已移除步變量已輸入變量已移除方法1x3逐步（準(zhǔn)則:F-to-e nte

7、r的概率=.150,F-to-remove的概率=.200）2x1逐步（準(zhǔn)則:F-to-e nter的概率=.150,F-to-remove的概率=.200)3x6逐步（準(zhǔn)則:F-to-e nter的概率=.150,F-to-remove的概率=.200)4x4逐步（準(zhǔn)則:F-to-e nter的概率=.150,F-to-remove的概率=.200)a. 因變量：y表1是逐步回歸每一步進(jìn)入或剔除回歸模型中的變量情況。表2模型統(tǒng)計(jì)量步RR平方調(diào)整后R平方估計(jì)標(biāo)準(zhǔn)誤差1a.995.990.9904906.9165821.000 b.999.9991226.8458631.000 c1.000.9

8、991110.508774d1.0001.0001.0001062.33830a.預(yù)測(cè)值:（常數(shù)），x3b.預(yù)測(cè)值:（常數(shù)），x3, x1c.預(yù)測(cè)值:（常數(shù)），x3, x1, x6d.預(yù)測(cè)值:（常數(shù)），x3, x1, x6, x4e.因變量y表2是逐步回歸每一步的回歸模型的統(tǒng)計(jì)量表3方差分析表步平方和df均方F顯著性1回歸.0061.0061719.369.000 b剩余409323115.7081724077830.336總的.713182回歸.5892.29513880.306.000 c剩余24082412.124161505150.758總的.713183回歸.9063.9691129

9、5.406.000 d剩余18498445.808151233229.721總的.713184回歸.4244.8569257.835.000 e剩余15799877.289141128562.664總的.71318a.因變量yb.預(yù)測(cè)值:（常數(shù)），x3c.預(yù)測(cè)值:（常數(shù)），x3, x1d.預(yù)測(cè)值:（常數(shù)），x3, x1, x6e.預(yù)測(cè)值:（常數(shù)），x3, x1, x6, x4表3是逐步回歸每一步的回歸模型的方差分析，顯著性概率是0.00,表明回歸極顯著。表4回歸方程系數(shù)步非標(biāo)準(zhǔn)的回歸系數(shù)標(biāo)準(zhǔn)的回歸系數(shù)t顯著性B標(biāo)準(zhǔn)誤Beta1（常數(shù)）8346.4351680.2364.967.000x361.

10、8031.490.99541.465.0002（常數(shù)）2925.980539.7015.421.000x345.0801.110.72640.623.000x1.737.046.28615.998.0003（常數(shù)）1032.9091014.9511.018.325x340.0202.582.64415.502.000x1.694.046.26914.934.000x6.732.344.0982.128.0504（常數(shù)）722.073991.516.728.478x344.3633.740.71411.862.000x1.761.062.29512.279.000x6.630.336.0841.875.082x4-.085.055-.081-1.546.144a.因變量: y表4是逐步回歸每一步的回歸方程系數(shù)表。五、模型分析1.建立回歸模型：y =+ bnxn +、一 + b 益 + e根據(jù)多元回歸模型：1122火k從表4中看出，過程一共運(yùn)行了四步，最后一步以就是表中的第4步的計(jì)算結(jié)果得知：7個(gè)變量中只進(jìn)入了 4個(gè)變量和。把表4中“非標(biāo)準(zhǔn)化回歸系數(shù)”欄目中的“ B”列數(shù)據(jù)代入多元回歸 模型得到方程:y = 722.073 + 4 4.363xQ + 0.761%】+ 0.6