What is the average monthly salary?

"The average monthly salary of women in 2023 is 8689 yuan."

"In 2023, the average monthly salary of women in front-line and new-line workplaces will be 18903 yuan."

Have you averaged the above data? Recently, some recruitment platforms released statistical data, which triggered the anxiety of netizens-"Sorry, it delayed the country again."

Some sharp-eyed netizens point the finger at the "average monthly salary" of inflated data. Indeed, the average monthly salary is almost always the most unpopular and controversial data. As many people ridicule, it is meaningless to make the average monthly salary of migrant workers and Musk with a monthly salary of 3,000 yuan. In statistics, it is the median rather than the average that represents the overall level.

But the data is not in line with the reality, and we can't blame the average calculation method. If you compare the official average data, you can clearly see how unreliable the average data of the recruitment platform itself is.

According to the Survey Report on Women's Workplace in China in 2023 released by Zhaopin, the average monthly salary of women in 2023 was 8,689 yuan, while that of men was 9,942 yuan.

In the Insight Report on Women in First-tier and New First-tier Cities released by Lagou Recruitment, in 2023, the average monthly salary of women in first-tier and new-tier workplaces was 18903 yuan, and that of men was 2237 1 yuan.

According to the average wage data of 20021year published by the National Bureau of Statistics, the average annual wage of employees in urban non-private units in China in 20021year was 106837 yuan, and that of employees in urban private units in China in 20021year was 62884 yuan. This average data is far lower than the average data released by the recruitment platform.

Obviously, the statistics released by the recruitment platform are ridiculously high, which is not just an "average" problem. Its statistical samples and statistics determine that the statistical results never represent the general public.

Take hook recruitment data as an example. The report shows that its data collection samples come from four first-tier cities of Beijing, Shanghai, Shenzhen and Guangzhou and five new first-tier cities of Hangzhou, Chengdu, Wuhan, Nanjing and Suzhou. According to Beijing Youth Daily, the data sample is mainly for recruiting users, and 8 1% of them have bachelor's degree or master's degree, and less than 20% have junior college degree or below. From the perspective of working years, 80% of users have more than 2 years of Internet work experience, so the overall salary level is relatively high. Lagou Recruitment also published a data sampling survey, with a sample size of 8,437 people and 2,583 valid data.

It is not surprising that the conclusions drawn by specific groups and a small number of samples are not in line with public cognition.

The conclusion basis of Zhaopin's recruitment of "the average monthly salary of women is 8689 yuan" was not disclosed. Whether the sample is representative or not and whether the sample size is reasonable is also questionable.

These key messages are ignored or deliberately hidden in the communication process, which leads to unnecessary anxiety and gives people the illusion of "mixing too badly".

As a data publisher, I am well aware of the limitations of these data. Maybe this restriction is just what they want. Because data is related to platform interests and business demands, the purpose is to attract more enterprises or job seekers to settle in. Its essence is a kind of platform propaganda, which is only presented in a seemingly objective "research data" package. Since it is "Wang Po selling melons and boasting", the higher the salary data, the better. Its subtext is still-we have high-paying positions here. Come and have a look.

Therefore, for the recruitment platform statistics, in an outdated phrase, "if you are serious, you will lose." No wonder some experts can't stand it. They called on the statistical data released by the platform to ensure that the number of samples is large enough, and the release should be professional, objective and fair, so as to avoid generalizing.