The Calculations

Here, I’ll describe the various calculations that are performed on the different models. To hopefully make it easier to picture how each model functions, the various calculations are described below. At the bottom of the page, the models are listed and assigned their respective calculations. Hopefully you’ll see what I mean as you read.

View, Research, & Browse Model:
There is no calculation involved in this model

This is, essentially, just a compilation of ABA data

You can sort and filter, but nothing is changed or calculated

Dynamic Ranking Calculations:
3YA Employment Averaging: All employment data from 2020, 2021, 2022, is added together, and divided by the sum of graduates from those three years. In future years, the oldest year will drop off, and the newest year will be added. I.e., in 2025, the calculated years will be 2024, 2023, and 2022.

COA estimation: tuition, fees, and living expenses (living expense estimation provided by the ABA, currently only the cost of full-time residence on campus is included) are added together (T+F+L). Average grant amount is multiplied by the total percentage of students receiving aid (GrAvg x G%). GrAvg x G% is subtracted from T+F+L. Final equation: Total estimated COA = (T+F+L)-(GrAvg x G%). Due to ever-increasing costs, only the most recent year is included here. Historical data is interesting, but highly unlikely to be of practical benefit to anyone.

Dynamic Ranking Method: All schools are sorted by a metric, and a rank is assigned based on this position. This is repeated for each available metric, so a school that has the most expensive tuition, and the highest BL/FC outcomes, with received the “Base Ranks” of; 196 in the Tuition metric, and 1 in the BL/FC metric. When weights are assigned to each metric via the sliders, the associated rank for each school is multiplied by the schools’ Base Rank in that metric, resulting in each school’s “Weighted Rank”. After this, the Weighted Ranks are averaged together, to give each school a “Dynamic Weighted Sum”. Lastly, this Dynamic Weighted Sum is ordered, and each school is assigned a rank from 1 to 196 based on the position of its Dynamic Weighted Sum. To clarify, in the MRD model, only the most recent year data affects this calculation. In the 3YA model, the employment outcome data used for ranking is the result of the 3YA Employment Averaging calculation.

Location Data:
Locational Guidance: Each school is plugged into Power Bi’s Map Visual. There are a handful of schools for whom this data results in strange outcomes (such as Cardozo being located in India on the map). The size of a school’s “bubble” is determined by the percentage of graduates who work in that school’s primary employment location (universally the state in which the school is located). Secondary and tertiaty employment locations, as well as percentages, can be found by hovering over the bubble. Additional usage instructions can be found in the “Locational 3YA Guide”, the final slide of the 3YA model window.

Calculations By Model