Salary data for all Ladder Rank and Professor of Teaching Faculty in the Samueli School of Engineering are plotted below.
As a function of rank, step, and gender:
As a function of rank, step, and ethnicity:
Multiple Linear Regression Analysis
As indicated in Table 1, the simplest model with only demographic variables shows that relative to white male faculty, women earn salaries that are around 7.6% lower, Asian faculty 9.4% and URM faculty earn 14.1% lower. The proportion of salary variation explained by this model was 7%. After all control factors are added, 93% of salary variation is explained by a model with demographic, experience, field, and rank variables. After adjusting for covariates, relative to white male faculty, salaries are around 2.5% higher for faculty who are women, 0.3% higher for Asian, and 0.4% higher for URM faculty. This model also shows that demographic variables are not statistically significant determinants of faculty salary. The final model predicted salaries within plus or minus 17.3%. (For technically-minded readers, the RMSE on the log base 10 scale is 0.035)
Progression Analysis
The progression data for all Engineering Ladder Rank and Professors of Teaching Faculty, are plotted below. Normative progression is defined in the Progression Matrix.
Progress by gender:
Progress by ethnicity:
Progress Rate Analysis
The results indicate that there is no statistically significant difference in progression rate means by either gender or ethnicity when compared to white male faculty. Normative progression is defined in the Progression Matrix.
