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每個學(xué)校的標(biāo)準(zhǔn)很多都是不一樣的，需要具體問題具體分析

一家一個標(biāo)準(zhǔn)

以下是niche網(wǎng)上的計算方法，Ａ檔要求Ｚscore 在20%以上。

“How Do We Calculate Rankings and Grades?
Our rankings and grades are calculated using a series of steps to ensure statistical rigor and useful guidance in the school choice experience. In general, the process used to calculate each ranking was as follows:

First, we carefully selected each ranking’s factors to represent a healthy balance between statistical rigor and practical relevance in the ranking.
Next, we evaluated the data for each factor to ensure that it provided value for the ranking. (The factor needed to help distinguish schools from each other and accurately represent each school.) Because there are different factor types, we processed them differently:
Factors built from Niche user data and student/parent-submitted surveys were based on aggregated data/responses across each school. We logically have a higher degree of confidence in the aggregated score for schools with more responses, so a Bayesian method was applied to reflect this confidence.
Factors built from factual information were inspected for bad data including outliers or inaccurate values. Where applicable, this data was either adjusted or completely excluded depending on the specific data.
After each factor was processed, we produced a standardized score (called a z-score) for each factor at each school. This score evaluated distance from the average using standard deviations and allows each school's score to be compared against others in a statistically sound manner.
With clean and comparable data, we then assigned weights for each factor. The goal of the weighting process was to ensure that no one factor could have a dramatic positive or negative impact on a particular school’s final score and that each school’s final score was a fair representation of the school’s performance. Weights were carefully determined by analyzing:
How different weights impacted the distribution of ranked schools;
Niche parent and student user preferences and industry research;
After assigning weights, an overall score was calculated for each school by applying the assigned weights to each school's individual factor scores. This overall score was then assigned a new standardized score (again a z-score, as described in step 3). This was the final score for each ranking.
With finalized scores, we then evaluated the completeness of the data for each individual school. Depending on how much data the school had, we might have disqualified it from the numerical ranking or from the grading process. Here is how we distinguished these groups using the weights described in step 4:
Schools missing the data for 50 percent or more of the factors (by weight) were completely excluded. They did not qualify for the numerical ranking or a grade.
Schools that had at least 50 percent of the factors (by weight) but lacked one or more of the required factors were not included in the numerical ranking but were assigned a grade according to the process outlined in step 7 below.
Schools that had all of the required factors (by weight) were deemed eligible for both a grade and a numerical ranking.
Lastly, we created a numerical ranking and assigned grades (based on qualifications discussed in step 6). Here is how we produced these values:
The numerical ranking was created by ordering each school (when qualified) based on the final z-score discussed in step 5.
Grades were determined for each school (when qualified) by taking the ordered z-scores (which generally follow a normal distribution) and then assigning grades according to the process below.”