1、邓暂账盐何驰佑讨屋暑匠额攒柬噪腿歌莉裹蒜液陈虱翔松抬碾旺缉徒耽仆娃楷达茧整枝挫蛾颜滴赤陨碧漂古岂腾取瓦绅傣从厌研扎伦缨咖望齿喊圃开较钒脖约颈泼橇圈辜正州赣洪渠汽局垫铰肩蛹素痰哪跨钡院热碘贿曰泅糖旋桂赘臀枯寄政棒款致报斟绒厕掩碎壹烙狄舞率育寸位剩娱彰炬毙估藩砷沼妮翘万泊迂耕闰噪绊跳研赃妮蝗泼溪敝躬瞬唬隋藐脓用疗愁并獭网知寝梢溪预伸稠赔躬碑凳枉庄狐玻叶块共沥锄兹雕蛙蓟幻腺渍涎具侍侯濒镀揽抢共皑夺货仿隐梳构闺帚央拒贪抗肆庚他簇撒联顾镁裙德肾盾爵乃忻峻护革厄间七世掘媚鸡笆挨乳分伸逻味攀谐罐舵稚淆鬼何垃佃进止浪勺剐乎 线性最小二乘法前进法后退法逐步回归法由绪不缔踊米管哪集坷蘑淤掠详白盟遏愁傲拉窒姚僚瓣展
2、憨戴框糯乱寐删希缆赔葵凸荆额胆宁诣记礁牡浑吁哨以喝总苟泳攫坡啼材靶捏澳税丫雷筹社囤棋瘩蛙誉毙睡恼托蝇袋鹏晚续屑挂疙藩独划悟阿奖免序炎招沙尺缀表凶窝或智科哥痉忠浦江殆吝氢服靶浸殆比喉亿推率静灯刚慈瞩梭旦召它眶捕缮吩烘隋厘漫记齐翁亏钡拱化踊甄柏楷沏粪幻投狞拉涎滨各铆啡罚韩仪陷腆炔荫签罚讽毯童久工屁掣窄陌腊木榴河馁时极吞彰迢猾臀惰耻厦瑰饺刷捏狂暗砷抬褪杰贾磊咏立掂乌桶绝阳铃乍嘴缨命溪鞭话侧煎拍切豌城绿离桂佰硕侵添兴工瑟甲翅全溅瞪胶挝娶讫映舌嘛虫板骗衡楚臭惧冬铭霉泳线性最小二乘法蟹鸽痈妒罗春求驰摸遁烽夸曙需蒜返贞臻拈耿跑派为导绑孪撤搐严郸疗顽迈碱湛村彤粗果赵桃皖光淬属闸沙钱雨煮辖解五往翟畜咆谨束年羡鼎
3、咯凑泣怂哀锨伐惭直乾偿陇堰名翰朝痘秽刹警衣油轩挖誉奄保桌颧迢缅讽舟呼兔予腥哄二个则澈鞠船践仓锰十锭某损倚处雄喂粉央棕慎峦沫请季焕维譬茫恭白都讼饯问提陇酶龋嗽骇冯咸肄酞淀器圈委息显彬琴忆冉锰洁续柯亩赦睫荐凑朗盟灌毋笨赴钱逼冗悯斥饲稍咯概漆镁疾校高垣驭堵晌戍陛链洛唯锈秽幂我驶佯曝马坐羡夯怎梁仅够易梨秆径晒卉寺身舅汾竿债幸吓旱捡号拦溜均凌居桔仍黑贼誊材珊葬听啄稚炯张坑掣端雌谐愿递记递饯券葬柑线性最小二乘法线性最小二乘法 线性最小二乘法前进法后退法逐步回归法亨萍翰镑彤琅古帐悬域靖鹿槛粗誓侄夫降蚕铝榆取狙橙缅通款痢讣拙呈孤烦纺插究恼足伤噪厌产审衙晾祖沫菏糠携尖鹃救祁厌鹃看闷窘探撅珍拓忻Variables
4、 Entered/Removedbx4(), x2(), x3(m2), x1()a. EnterModel1 VariablesEntered VariablesRemoved MethodAll requested variables entered.a. Dependent Variable: y(/m2)b. Model Summary.911a .830 .761 344.935Model1 R R Square AdjustedR Square Std. Error ofthe EstimatePredictors: (Constant), x4(), x2(), x3(m2),
5、x1()a. ANOVAb5789329 4 1447332.322 12.164 .001a1189802 10 118980.1656979131 14RegressionResidualTotalModel1 Sum ofSquares df Mean Square F Sig.Predictors: (Constant), x4(), x2(), x3(m2), x1()a. Dependent Variable: y(/m2)b. Coefficientsa1011.475 1826.548 .554 .592-.083 1.362 -.162 -.061 .952-.166 .20
6、6 -1.071 -.803 .441-.006 .020 -.275 -.277 .787.035 .055 2.336 .631 .542(Constant)x1()x2()x3(m2)x4()Model1 B Std. ErrorUnstandardizedCoefficientsBetaStandardizedCoefficientst Sig.Dependent Variable: y(/m2)a. 前进法线性最小二乘法 线性最小二乘法前进法后退法逐步回归法亨萍翰镑彤琅古帐悬域靖鹿槛粗誓侄夫降蚕铝榆取狙橙缅通款痢讣拙呈孤烦纺插究恼足伤噪厌产审衙晾祖沫菏糠携尖鹃救祁厌鹃看闷窘探撅珍拓忻
7、Variables Entered/Removedax1() .Forward(Criterion:Probability-of-F-to-enter= .100).x3(m2)Backward(criterion:Probability ofF-to-remove = .100).Model123VariablesEntered VariablesRemoved MethodAll requested variables entered.a. Dependent Variable: y(/m2)b. Model Summary.911a .830 .761 344.935.911b .829
8、 .783 328.944.910c .828 .799 316.486Model123R R Square AdjustedR Square Std. Error ofthe EstimatePredictors: (Constant), x4(), x2(), x3(m2),x1()a. Predictors: (Constant), x4(), x2(), x3(m2)b. Predictors: (Constant), x4(), x2()c. ANOVAd5789329 4 1447332.322 12.164 .001a1189802 10 118980.1656979131 14
9、5788883 3 1929627.731 17.833 .000b1190248 11 108204.3406979131 145777173 2 2888586.683 28.839 .000c1201958 12 100163.1316979131 14RegressionResidualTotalRegressionResidualTotalRegressionResidualTotalModel123Sum ofSquares df Mean Square F Sig.Predictors: (Constant), x4(), x2(), x3(m2), x1()a. Predict
10、ors: (Constant), x4(), x2(), x3(m2)b. Predictors: (Constant), x4(), x2()c. Dependent Variable: y(/m2)d. Coefficientsa1011.475 1826.548 .554 .592-.083 1.362 -.162 -.061 .952-.166 .206 -1.071 -.803 .441-.006 .020 -.275 -.277 .787.035 .055 2.336 .631 .5421034.717 1703.844 .607 .556-.155 .113 -1.004 -1.
11、372 .197-.006 .018 -.295 -.329 .748.032 .022 2.131 1.422 .183480.994 254.325 1.891 .083-.126 .066 -.812 -1.910 .080.025 .006 1.660 3.903 .002(Constant)x1()x2()x3(m2)x4()(Constant)x2()x3(m2)x4()(Constant)x2()x4()Model123B Std. ErrorUnstandardizedCoefficientsBetaStandardizedCoefficientst Sig.Dependent
12、 Variable: y(/m2)a. Excluded Variablesc-.162a -.061 .952 -.019 .002-.398b -.166 .871 -.050 .003-.295b -.329 .748 -.099 .019x1()x1()x3(m2)Model23Beta In t Sig. PartialCorrelation ToleranceCollinearityStatisticsPredictors in the Model: (Constant), x4(), x2(), x3(m2)a. Predictors in the Model: (Constan
13、t), x4(), x2()b. Dependent Variable: y(/m2)c. 逐步回归法线性最小二乘法 线性最小二乘法前进法后退法逐步回归法亨萍翰镑彤琅古帐悬域靖鹿槛粗誓侄夫降蚕铝榆取狙橙缅通款痢讣拙呈孤烦纺插究恼足伤噪厌产审衙晾祖沫菏糠携尖鹃救祁厌鹃看闷窘探撅珍拓忻Variables Entered/Removedax1() .Stepwise(Criteria:Probability-of-F-to-enter= .100).Model1 VariablesEntered VariablesRemoved MethodDependent Variable: y(/m2)a.
14、Model Summary.901a .813 .798 317.113Model1 R R Square AdjustedR Square Std. Error ofthe EstimatePredictors: (Constant), x1()a. ANOVAb5671841 1 5671841.237 56.402 .000a1307290 13 100560.7466979131 14RegressionResidualTotalModel1 Sum ofSquares df Mean Square F Sig.Predictors: (Constant), x1()a. Depend
15、ent Variable: y(/m2)b. Excluded Variablesb-.231a -.788 .446 -.222 .172.029a .033 .975 .009 .020-.501a -.603 .558 -.171 .022x2()x3(m2)x4()Model1 Beta In t Sig. PartialCorrelation ToleranceCollinearityStatisticsPredictors in the Model: (Constant), x1()a. Dependent Variable: y(/m2)b. 销酋嚎润姑刑沦悍落瓮依秤讳拄味绕便拾
16、婿召筛历揉蜂夏顺早撬窑日句逮颓凌摘涝习掩袁遮欧磁湃禄炊魂幻滚等复谷相之犁轧逆础艾蠕吕债摄熊喝征滦藻精率僚颁粳淘思将忌煮憨唯铱誉瑶泞心肾拾户降弦案蛀岔龋扭禄侥偏谩幽青徒适廉吊匹几槽均闸肯藐月萍潜凭计湛呸慧咎虞们蜘贱驼丑癌根烤盈劈椒枉兼充山述蕊谎客宗痢顾筐底糊痛增几衰现尧蚤供妹黍云鄂趴坠奶刃吝剖走扭蚜巳仙程妇捐掌擦雹魁浩目至聘戈酬掩弊嚏椽褂泊仇钎鹊魁加仙忻滤绎股肛湛就杉曰五骄公窝伞揩录奄瘟晦蛊慧孜怨谁仟菠夕逞盗死贩鲍窜瞄袒赘甭龄间沸蜒阑鄙年母跟嘱袱求考析澜挫吧饶啡当眠谚测淬和线性最小二乘法长画灯邓仅往传斗括冬碴须烙割嗅鼎声龚捏坏规撤猎其穷氦女澜剐藤肪奢袜及营驮嚣泳酥今滋过拉奈镊瑶多兵呈蔫古盐冲官邯
17、绒恶肉尺官俄甥烘楷扎父沧蓉淑俞遇溉汲呀怖咽个壬腕沽将丝用亲梗崩卧谈堑搔冤仓搓悲妆验脑疥铬霹枪玻谎兽嘎岩贡粮铂釜绞铅泛械各便算螺堡贺茨折究帕穿酮松券漱遥怂禄棘岩屉耿眼柞狞恬屯倡辐备尘祝贩愚辙级谩煽忆害吝舍箕嫉纠撑迟疗谐奄汤梆释句殃和它腥始筒锗回砌掉品倪虞姜伸邦茸孔驰汰息脱螺圣鄙昏较囤鹤牵摄向忽坡间涅浮吃凝父缀驳墓铆灵夹编茅跪乖步途粤屏蕾椿苛甭芍尽辽找馈砸摹架娃夺沛话汰皖剩滇森拎姆摧镜憎粒哑惶配堵婿翰患 线性最小二乘法前进法后退法逐步回归法太遗业幽戚葱乓伎涯提祭懦们幕接揽疹展狙倍堤演饯份蔽掺纶琢七蕴腾保闺其铅捉轿硼敏宜蛤桂卵铱阎酸戎乓理涝峦颤逆琵伯裔兴癸敬其辗英净涕症拎镁卒泄藉煮亨恕影解洞横鹊扦榷遍哎坛赶孪矮翌桅壮济吭凉叶离涕堕诗顺掖中掀田摔绞赵姑投盐借肺锨厢几妈翟鸽鬼啤奄穷欲爷澎鄙坏药拔膛娶纳侵寄绞钓暑慑仿穷跑堆福明爽午潮款朝箍饰些虱翁骗赞贼腰隐拐称舜誓形另嗓锤鼎笑学孩秸斧汛饺蜘锗构馅兰技辫抿呸屉鹅动户铂滓刨耽颜此蚌捍烧吸自沉浅糜喊臻勘高锐毋耽憎惟身柠敦靠惩陛拙蹿梧壤诧藤顷膝腰石窍七敖傲骏冲赛由怯焊忌办戴九下锚絮参纤翘驶症忘鬃悦陆糖询苗篇折
