Regression analysis revealed a strong correlation between so

计量经济学的S.E of regression怎么算?

图中的其他空我都算出来了,就是S.E.of regression 没算出来,回归标准差怎么算啊?

求翻译multivariate logistic regression analysis using a stepwise backward metod
怎么翻译
1.multivariate logistic regression analysis using a stepwise backward metod
2.Multiple logistic regression
3.cox regression model
4.erosive gastritis

least squares linear regression应该如何代值算?比
least squares linear regression应该如何代值算?比如这道题.

Linear regression analysis (abscissa at origin)
什么叫横坐标在原点?

回归F值检验的含义
Sum of Squares df Mean Square F Sig.
Regression 11.881 5 2.376 16.57 .000a
Residual 6.165 43 .143
Total 18.046 48
请问这个表能说明什么?特别是F值是16.573能表示什么?本人初学,见笑了!
Model Sum of Squares df Mean Square F Sig.
1 Regression 11.881 5 2.376 16.573 .000a
Residual 6.165 43 .143
Total 18.046 48

英语高手进来帮我看看
高手帮我看看：
回归自然是不是Regression nature
回归生活是不是Regression life
翻译是对还是错?
如果不对,能否告诉我回归生活和回归自然的英文?

需要用R语言做Regression的讲解材料.
请帮忙找一份用R语言组Regression的讲解材料,老师讲话讲不清楚,听不懂,板书也特奇葩,没办法只能尽量自学了.请尽量详细通俗一些.
对了,我是文科本科生,在念商科硕士.

数学关于least squares linear regression的题
when purchased,an automobile is valued at $1500.Its value depreciates at the rate shown in the table below.Based on a least squares linear regression,what is the value ,to the nearest hundred dollars,of the automobile when t=4?
time t 0 1 2 5
(years)
value v(t) 15000 13000 10900 3000
(dollars)
怎么算的怎么算的
大恩人快救救我~

英语翻译
Calculating the linear regression equation between the copper
supplementation (x) and the percentage improvement of the
average daily body weight gain (y) and feed conversion (y)
respectively

proportional odds ordered logistic regression model怎么翻译?是什么logistic回归模型

meta regression 什么意思
麻烦高手翻译下这句话: We used fractional polynomials in a meta-regression to determine the dose-response relationships by sex and end point using lifetime abstainers as the reference group.
to determine the dose-response relationships by sex and end point 应该是 按性别和终点决定剂量反应关系
using lifetime abstainers as the reference group 应该是 将终身戒烟者作为对照组
不过以上都是专业方面的东西,谢谢大家,至少我知道mata-regression是什么了:)

英语翻译
5、10.92 Regression through the origin (Flour2) .Sometimes it is known from theoretical considerations that the straight-line relationship between two variables,x and y,passes through the origin of the xy-plane.Consider the relationship between the total weight of a shipment of 50-pound bags of flour,y,and the number of bags in the shipment,x.since a shipment containing x=0 bags (i.e.no shipment at all) has a total weight of y=0,a straight-line model of the relationship between x and y should pass through the point x=0,y=0.in such a case you could assume and characterize the relationship between x and y with fhe following model:
The least squares estimate of for this model is ,from the records of past flour shipments,15 shipments were randomly chosen.

英语翻译
The second column of Table 2 presents the OLS regression results and incorporate White-corrected
standard errors to correct for heteroscedasticity.The results show that the more capacity a firm
commits the less aggressively it bids in an auction.The effect of backlog on bids is small but consistent with the theory in Pitchik and Schotter (1988) that attributes less aggressive bidding to
budgetary restrictions.It is also consistent with the findings Jofre-Bonet and Pesendorfer (2000).
Looking at the afternoon bidding dummies,we find that firms that win in the morning bid more
aggressively in the afternoon.However,it is probably the case that our measure of backlog is not fully
controlling for differences in firm efficiencies and that the negative coefficient on this variable reflects
differences in overall efficiencies (winners vs.losers) as opposed to differences in the bidding
behavior in the morning and afternoon.To correct for this potential,we estimate the model withfirm-time period effects.As discussed above,these effects should control for differences in
unobserved heterogeneity across firms on a given auction day.In contrast to the OLS results which
exploit cross firm variation in bids,the fixed effects results allow for a comparison of bidding
behavior in the morning and afternoon for a given bidder.The results are presented in column 3.The
findings suggest that,on average,those firms that lost in morning sessions bid more aggressively,
relative to their morning bid,than those firms that won at least one project.The winners of early
auctions are typically the stronger bidders and conditional on the outcome of early auctions,the weak
bidders (i.e.the morning losers) adjust their strategies and bid more aggressively in afternoon
auctions.In addition,the fixed effects results suggest that the more competitive the set of rivals a firm
faces the more aggressively the firm bids.These results are consistent with the prediction in Maskin
and Riley,(2000,proposition 3.5) which suggests that if a weak bidder faces a strong bidder rather
2 than another weak bidder he will bid more aggressively and vice versa.

计量经济学计算题--回归结果中求F ,S.E.regression...
如上 给出回归结果：
R-squared 0.66325 Mean dependent var 5.123810
Adjusted R-squared S.D.dependent var 3.694984
S.E.of regression Akaike info criterion 4.505098
Sum squared resid 91.95205 Schwarz criterion 4.604576
Log likelihood -45.30353 F-statistic
Durbin-Watson stat 0.858742 Prob(F-statistic) 0.000007
要求R^2,F,S.E.等值 应该怎么求啊?

origin曲线拟合
lynomial Regression for DATA1_B:
Y = A + B1*X + B2*X^2
Parameter Valuex09Error
------------------------------------------------------------
Ax090.97253 0.2493
B1x09-0.0126 0.00617
B2x091.14061E-4 3.77615E-5
------------------------------------------------------------
R-Square(COD)x09SDx09Nx09P
------------------------------------------------------------
0.93824x090.02096x0912x09

Beta is quantified as the slope of a linear regression of the form:如何翻译?

英语翻译
Multiple linear regression analysis shows that there is a reasonable linear correlation between E2 (or SN2) overall barriers and the linear combination of PA of X- and electronegativity of the
central atom.