会计专业英语翻译（很急啊）

999999~~急！急！非常急！麻烦各位英语牛人帮忙啊！！！翻译下面这几段的机械类的英语，在线等，在线等，急用！
要求： 要比较专业的翻译，不要用机器翻译的，谢谢啦~~~~~~

Multiple discriminant analysis as an extension of linear discriminant analysis was applied with stepwise backward option. This means that a model of discrimination is built step-by-step. At the beginning, all variables are included in the model and then, at each step, the variable that contributes least to the prediction of group qualification is eliminated (F enter/remove value 0.05). Thus, as the result of a successful discriminant function analysis only the most important variables are in the model, i.e. only those variables that contribute the most to the discrimination between good and bad companies. The following discriminant functions are obtained:
（公式略）
where:
PERFORMANCE = aggregate score of company's financial performance (ACCR - based on accrual ratios; CF- based on cash flow ratios)
P = profitability latent variable
E = efficiency latent variable
S = solvency latent variable
I = excellence latent variable
FD = financing debt latent variable
QE = quality of earnings latent variable
As it can be seen from the function, in accrual ratios model (PERFORMANCEACCR), ratios grouped into factor solvency (S) have the greatest relative importance -weight (0.704) while latent variables of profitability (P) and efficiency (E) -have a slightly lower relative impact weight of 0.576 and 0.619 respectively. Profitability and efficiency have a positive impact on company's performance, meaning that performance will be better if these factor values are higher. Oppositely, impact of solvency factor on company's performance is negative, that is performance will be worse if solvency latent variable is higher. In efficiency latent variable interpretation, it is necessary to make in-depth analysis of the factor, because it contains two ratios with opposite intensity direction within a factor. Namely, interest coverage ratio (ICR) is positively correlated with the factor (0.849), while price to earnings ratio (PER) has negative impact in factor (-0. 1 79). As the higher value of PER ratio indicates greater number of years required to return investment, it is logical that the assessment of the company is worse as this ratio is greater. However, efficiency factor has a positive impact on the overall company's performance, because ICR has greater loading than PER ratio. Latent variable (L) consisting of liquidity ratios has no statistically significant impact to the discrimination between good and bad companies and it is excluded from the model because of stepwise backward option.
是会计类的啊，不是机械，打错了。

作为一线的判别式分析的延长的多重判别式分析用逐步的向后选择余地是应用。这个意味着那一个歧视的模范一步步地是体形的。从一开头，所有的变数被在的模范身上包含然后在每一步方面，最不向组资格证书的预言捐赠的变数被消灭(F 进入/从去除对的价值0.05）。由于一个仅成功地判别函数分析最对重要变数是的在的模范身上的星期四,即仅那些变数，其最向在好和坏公司之间歧视捐赠。下列的判别函数被为得到：（公式略）在那里：公司的财政表现的表现=聚集的得分 ACCR-基于自然增长对的比率；基于 CF 在上现金流转对的比率 P=有利潜在的变数 E=效率潜在的变数 S=清偿能力潜在的变数我=杰出的潜在的变数 FD=筹措资金债务潜在的变数 QE=品质的收入潜在的变数同样它罐被注意到从运转在中自然增长对的比率的模范（PERFORMANCEACCR）对的比率把分组变为做代理商清偿能力（S）富人很好亲戚对的重要性-weight（0.704）在的同时潜在的变数的有利（P）和效率（E）-havea 略微更低亲戚分别冲击0.576和0.619的重量。有利和效率让一正量冲击公司的表现意味着那表现将是较好，如果这些因素价值观是更高。对面地，清偿能力因素的对公司的表现的冲击是负,那个是表现的意愿是更坏，如果清偿能力潜在的变数是更高。在效率潜在的可变解释中，它是对对必要的做分析因素的深度分析，因为它用和相反强度方向在一个因素以内含有两对的比率。就是，在的权益覆盖范围对的比率(ICR）被表示赞同将与因素(0.849）相联系，与此同时向收入对的比率(PER）的价格有对负面影响在因素中-0。1 79。如 PER 对的比率的更高对的价值所示较大的许多年的数目被要求归还在上的投资，它是合乎逻辑那公司的对的估价是更坏，当这对的比率是较大时但是，效率因素让一肯定的对总公司的表现的冲击较大装载，因为 ICR 富人，与每对的比率相比。由流动比率构成的潜在的变数(L）有没有在统计上对重要对的冲击向在好和坏公司之间歧视和它被由于逐步的向后选择余地把排除在的模范外。

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