首页the t-value(absolute value) for testing the difference between mean salaries between males and females

the t-value(absolute value) for testing the difference between mean salaries between males and females

时间: 2024-06-07 18:06:47 浏览: 94

职业教育水平错配对俄罗斯应届大学毕业生收入的影响-研究论文

本文分析了横向工作与教育不匹配的决定因素和后果，这是有关教育和劳动力市场辩论中越来越相关的话题。这个问题反映了劳动力市场中教育领域和职业的衔接。我们使用俄罗斯全面且具有代表性的国家数据来评估工作与教育不匹配的决定因素及其对大学毕业生工资的影响。该研究基于毕业生的评估和统计分析。我们发现，俄罗斯三分之一的毕业生从事的工作与他们的研究领域无关。此外，来自产生更多一般人力资本（社会科学、商业、法律、服务）或低薪常见领域（农业）的毕业生更有可能处于这种情况。相反，来自产生特定人力资本的领域（例如：医学）的毕业生更有可能被匹配。我们发现错配对大学毕业生的收入有负面影响，错配程度越高，对错配的惩罚就越高。该研究表明，除了低收入领域（例如：农业）外，大多数领域都会对错配进行处罚。

To calculate the t-value for testing the difference between mean salaries between males and females, you would need to perform a two-sample t-test. The formula for the t-value is: t = (x̄1 - x̄2) / (s^2pooled * (1/n1 + 1/n2))^0.5 where: - x̄1 is the mean salary for males - x̄2 is the mean salary for females - s^2pooled is the pooled variance of the two samples - n1 is the sample size for males - n2 is the sample size for females To calculate the pooled variance, you would use the formula: s^2pooled = ((n1 - 1) * s1^2 + (n2 - 1) * s2^2) / (n1 + n2 - 2) where: - s1^2 is the variance of the male sample - s2^2 is the variance of the female sample Once you have calculated the t-value, you can compare it to the critical value from the t-distribution with (n1 + n2 - 2) degrees of freedom and a significance level of your choice (e.g. 0.05) to determine whether the difference between the mean salaries is statistically significant. If the absolute value of the t-value is greater than the critical value, then the difference is statistically significant, and you can reject the null hypothesis that the mean salaries are equal between males and females.

阅读全文