Ladder Rank Salary Data
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 0.5% higher, Asian faculty earn 13% and URM faculty earn 13% lower. Only 6% of salary variation is explained by this model. After all control factors are added, 94% 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 1% lower for faculty who are women, 2% higher for Asian, and 5% lower for URM faculty. This model also shows demographic variables are not statistically significant.
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 by gender when compared to white male faculty. However, URM faculty progress at a rate that is 2.4 years slower than white males (p = .020). Normative progression is defined in the Progression Matrix.
