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2018 US News Best Colleges rankings have been released


Replies to: 2018 US News Best Colleges rankings have been released

  • hzhao2004hzhao2004 Registered User Posts: 498 Member
    CalTech and Chicago have the highest average SAT because they don't recruit athletes.
  • Much2learnMuch2learn Registered User Posts: 4,426 Senior Member
    @hzhao2004 "CalTech and Chicago have the highest average SAT because they don't recruit athletes."

    Partially, but at least in the case of Chicago, they weight test scores a lot higher most school in the admission process. That is why they don't release gpa data in their CDS. In contrast, Penn weighs gpa more heavily but is more flexible on test scores. I think on average, Penn's approach makes better admission decisions, but Chicago is getting a bump in the rankings.
  • YnotgoYnotgo Registered User Posts: 3,538 Senior Member
    edited September 15
    I am curious about what spending numbers are used for Caltech by USNWR. Is that data available to people who pay to unlock some data?

    Caltech's operating expenses for 2015-2016 were about $2.5 billion all in, but that includes $1.87 billion for JPL expenses, which comes directly from the same amount granted to JPL by the US Gov't. (For 2017-18, word is JPL will get $2.1 billion.)

    Certainly, the presence of JPL is of value to Caltech undergrads in a number of ways, even beyond easy access to undergrad research there. But, perhaps the inclusion of JPL in Caltech's budget in some ways justifies the "logarithmic adjuster."

    If you subtract out the JPL budget, Caltech's spending per student (undergrad+grad) is about $287,000/year.

    Perhaps Berkeley's budget includes the budget for Lawrence Livermore National Lab, and so on for other national labs that are managed by universities. And, as mentioned, the budgets of many universities (but not Berkeley) include medical schools.
    But who -really- wants to go to Caltech??
    My kid is really looking forward to it, and leaves in 2 days. =((
  • foosondaughterfoosondaughter Registered User Posts: 235 Junior Member
    edited September 15
    @whatisyourquest Actually, although often used together, using a data transformation isn't the same as doing a curve fit. The purpose of a transformation is to alter the distribution to facilitate use, analysis, understanding and/or interpretation of the data while curve fitting is used primarily for modeling and extrapolation.

    Log transformations are commonly applied to percentages and ratios (such as the aforementioned spending/student metric) because those are often non-normal and values don't evenly reflect differences (especially at the "tails"). Standard inferential statistical tools and concepts (e.g., "z-scores") are not appropriate (or are difficult to interpret) for non-normal distributions.

    If a ranking system based on a maximum score of 100 points indicates 20% of its system is based a particular source of information, that is somewhat deceptive because it doesn't explain how that source's information is apportioned within the associated 20 score points. So (to use my YTAR example again), if I just apportioned the 20 points in the same manner as the raw YTAR value, Stanford would get the maximum 20 while Chicago would only get 9 points. Most other schools (with YTAR values less than 1) would receive 0 or 1 point. All of this doesn't mean the the YTAR is useless -- only that its distribution should be altered before being directly leveraged.

    [edited to remove link to en.wikipedia.org/wiki/Data_transformation_(statistics)#Reasons_for_transforming_data that didn't render correctly]

  • ChembiodadChembiodad Registered User Posts: 2,022 Senior Member
    According to USNWR, they utilized a set of 15 unique ranking criteria, but no school appears to have more than 5 shown on their respective page - without the complete data matrix this is no more valid than the black box that Forbes utilizes for their rankings.
  • whatisyourquestwhatisyourquest Registered User Posts: 612 Member
    @foosondaughter Got it. USNWR is using a data transformation, not a curve fit, which I had mistakenly assumed. I guess what I still don't understand is why a data transformation is justified because the data are non-normal. Even though a curve fit is not being used, it seems that the data are being altered to fit a normal distribution. Regarding your YTAR example, I don't see the problem with Stanford getting 20, Chicago 9, and most other schools getting 0 or 1. Let the chips fall where they may.

    Anyway, I'd have to dig into it more to understand, and I don't want to hijack the thread, so I'll not pester you with more questions. However, if you have a link that provides details of the USNWR data transformation and it's effect on rankings that would be very helpful. Thanks very much for the explanation!
  • moscottmoscott Registered User Posts: 860 Member
    @hzhao2004 @Much2learn Also don't put too much weight into Cal Tech and Chicago having the highest test scores. There's are higher because they superscore where a school like Yale does not.
  • Gator88NEGator88NE Registered User Posts: 5,431 Senior Member
    edited September 15
    @Ynotgo Schools have to report three categories of spending per FTE to IPEDS. US News likely uses this data or something very similar.
    Instructional Expenditures / FTE: “Instructional expenses” is a discrete reporting category. It includes expenditures for the colleges, schools, departments, and other instructional divisions of the institution and expenses for departmental research and public service that are not separately budgeted.  It also includes general academic instruction, occupational and vocational instruction, community education, preparatory and adult basic education, and regular, special, and extension sessions.  It includes expenses for both credit and non-credit activities.  It excludes expenses for academic administration where the primary function is administration (e.g., academic deans).  Information technology expenses related to instructional activities if the institution separately budgets and expenses information technology resources are included (otherwise these expenses are included in “academic support”).

    Student-Related Expenditures / FTE: This is an intermediate financial measure, including instructional, student services, and academic support expenditures, which is only available for public and not-for-profit institutions. The specific formula was developed by the National Center for Higher Education Management Systems (NCHEMS). Student-related expenditures are calculated as (Instruction + Student Services + Academic Support*(Instruction / (Instruction + Public Service + Research))).

    Educational and General Expenditures / FTE: This is a broader category, which includes the instructional expenditures listed above, plus expenditures for research, public service, academic support, student services, institutional support, plant operation & maintenance, and scholarships. This variable is also only available for public and not-for-profit institutions.

    You can search for the IPEDS data, but you can also use this link to compare schools. This link is useful, if a bit dated (2014 data), to do a comparison between several schools. Looking under the "Funding and Faculty" tab.

    Note that Stanford spends about the same amount as Caltech per FTE.

  • simba9simba9 Registered User Posts: 2,695 Senior Member
    Is that log 10 or log e?
  • MastadonMastadon Registered User Posts: 1,369 Senior Member
    edited September 16

    Since we are dealing with the effect of the mass of the JPL (Jet Propulsion Laboratory) on the rankings, the natural choice would seem to be log e... :\">

  • moooopmoooop Registered User Posts: 1,581 Senior Member
    Re Berkeley's drop, it's almost like somebody somewhere doesn't think it's cute and noble to start fires and scream because someone you disagree with is going to speak .
  • Penn95Penn95 Registered User Posts: 2,114 Senior Member
    ^berkeley has some issues with its undergrad program, most of which stem from the fact that it is a public university.
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