问题如下：
You built a linear regression model to analyze annual salaries for a developed country. You incorporated two independent variables, age and experience, into your model. Upon reading the regression results, you notice that the coefficient of experience is negative, which appears to be counterintuitive. In addition, you discover that the coefficients have low t-statistics but the regression model has a high \(R^2\). What is the most likely cause of these results?
选项：
A. Incorrect
standard errors
B. Heteroskedasticity
C. Serial
correlation
D. Multicollinearity
解释：
Age and experience are likely to be highly correlated. Generally, multicollinearity manifests itself when standard errors for coefficients are high, even when the is high.
可以把四个答案都分别解释下吗？
