Question

我正在寻找一些天才SQL帮助，我遇到了棘手的统计问题。

我要做的是从一组不平衡的用户配置文件中提取统计平衡的样本。一次为单个配置文件属性（例如性别）执行此操作会稍微简单一些。但是，同时跨多个维度进行此操作需要一些复杂性。

为了论证，让我说我有这张表。

Profile.userID  
Profile.Gender  
Profile.Age  
Profile.Income

如果我想从混合中提取一组配置文件，以便用户的新抽样大致匹配以下所有特征：

50% male, 50% female
30% young, 40% middle age, 40% old
40% low income, 40% middle income, 20% high income

有没有人对如何解决此问题有任何想法？

Answer 1

你所拥有的是抽样问题。他们解决这个问题的关键是将数据分成三个变量组合的单独组。然后，计算每组边际概率的乘积（您的值是边际概率）。然后，对所有18个组进行标准化。

例如，男性 - 年轻 - 低组的值将为0.5 * 0.3 * 0.4 = 0.06。您对所有18个组重复此操作，然后将其标准化为百分比（即，将每个值除以所有值的总和）。结果如下：

Gender  Age     Income  Marg    Normalized
Male    Young   Low     0.06    5.5%
Male    Young   Middle  0.06    5.5%
Male    Young   High    0.03    2.7%
Male    Middle  Low     0.08    7.3%
Male    Middle  Middle  0.08    7.3%
Male    Middle  High    0.04    3.6%
Male    Old     Low     0.08    7.3%
Male    Old     Middle  0.08    7.3%
Male    Old     High    0.04    3.6%
Female  Young   Low     0.06    5.5%
Female  Young   Middle  0.06    5.5%
Female  Young   High    0.03    2.7%
Female  Middle  Low     0.08    7.3%
Female  Middle  Middle  0.08    7.3%
Female  Middle  High    0.04    3.6%
Female  Old     Low     0.08    7.3%
Female  Old     Middle  0.08    7.3%
Female  Old     High    0.04    3.6%

然后这将成为每组的采样率。这是实际进行采样的伪SQL代码：

with SamplingRates (
    select 'Male' as gender, 'Young' as Age, 'Low' as income, 0.045 as SamplingRate,
    union all . . 
)
select t.*
from (select t.*,
            row_number() over (partition by gender, age, income order by <random>) as seqnum,
            count(*) over (partition by gender, age, income) as NumRecs
      from table t
     ) t join
     SampleRates sr
     on t.gender = sr.gender and t.age = sr.age and t.income = sr.income and
        seqnum <= sr.SamplingRate * NumRecs

Answer 2

以下是我如何去做，假设： 30％年轻，40％中年，30％年龄

采用最小公分母，您的泳池大小= 5x5x3x4x2x4 = 2400

您有18个查询将池填充到TEMP TABLE中。重复所有18个查询以获得更大的池。下面是理想池的分布情况以及每个查询的外观。您还可以在每个查询中引入一些随机性。有一篇关于这样做的帖子。

这可能不那么优雅，但应该产生一个平衡的游泳池。

您在伪代码中的第一个查询看起来像：

SELECT * INTO TEMP TABLE 
WHERE male, young, high income and ID NOT IN TEMP TABLE 
LIMIT RECORD SET 72

依此类推。希望能帮助到你。好问题。

CREATE TEMP TABLE
480 high income
    144 young
        72 males [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 72]
        72 females [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 72]
    192 middle age
        96 males [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 96]
        96 females [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 96]
    144 old
        72 males [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 72]
        72 females [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 72]

960 middle income
    288 young
        144 male [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 144]
        144 female [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 144]
    384 middle age 
        192 male [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 192]
        192 female [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 192]
    288 old
        144 male [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 144]
        144 female [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 144]

960 low income
    288 young
        144 male [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 144]
        144 female [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 144]
    384 middle age
        192 male [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 192]
        192 female [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 192]
    288 old
        144 male [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 144]
        144 female [SELECT THIS INTO TEMP TABLE WHERE ID NOT IN TEMP TABLE LIMIT 144]

SQL统计抽样

2 个答案: