Contribution: This article presents quantitative support that the changes implemented as part of Colorado State University's (CSU's) Revolutionizing Engineering Departments (REDs) grant produce statistically significant positive change through a series of nonparametric analysis techniques. Additionally, the set of nonparametric analysis techniques provides a novel approach to quantitatively analyzing student data after significant pedagogical changes are made to the undergraduate curriculum. Background: As part of the grant, a series of significant pedagogical changes were made to the electrical and computer engineering (ECE) undergraduate curriculum. A large portion of these changes relates to knowledge integration techniques, which are used to highlighting the intricate relationships between the three topics of electronics, signals and systems, and electromagnetics. This article presents an analysis of the outcomes that are in part due to these changes. Intended Outcomes: As a result of the grant and the associated curriculum changes, it was anticipated that the cumulative in-major grade point average for third-year students would increase. It was also anticipated that the in-major intercourse grades would be more positively correlated. The analysis techniques that were used provide novel examples of applications to student data. Application Design: The implemented changes described in this article directly follow from the goals of the National Science Foundation's RED program. Findings: Three nonparametric analysis techniques are performed on a collection of data from ECE undergraduates that was collected over 20 years. It is shown that the intertopical correlations between courses increase immediately following the implementation of the intervention discussed in this article, and statistically, significant evidence is presented supporting that the distribution of grades has positively changed following the intervention.