The salary data for all Ladder Rank Faculty in the Donald Bren School of Information & Computer Sciences are plotted below.
As a function of rank, step, and gender:
As a function of rank, step, and ethnicity:
Multiple Linear Regression Analysis
Multiple regression analysis of salary vs rank/step. 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 6.1% lower, Asian faculty 3.8% and URM faculty 6.9% lower. The proportion of salary variation explained by this model was 3%. After all control factors are added, 87% 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 0.5% higher for faculty who are women, 0.8% lower for Asian, and 0.2% lower 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 21.0%. (For technically-minded readers, the RMSE on the log base 10 scale is 0.041.)
Progression Analysis
The progression data for all ICS Ladder Rank Faculty, are plotted below. Normative progression is defined in the Progression Matrix.
Progress by gender:
Progress by ethnicity:
Progress Rate Analysis
Using a simple t-test, the results indicate that there is no statistically significant difference in progression rate means for women or Asian faculty compared to white male faculty. However, URM faculty progressed at a rate that is not as fast as that of White men. See note to Table 2 for additional analysis. Normative progression is defined in the Progression Matrix.
