If the WSJ presented something, I’d be more inclined to believe it. Forbes, not so much.
Let me add your quote here:
If you compare CS salary to salaries reported to the college as whole through student surveys, you’ll generally find they are similar when sample size is significant The bigger issue in my opinion is sample size is often not significant, particularly in smaller majors.
I have no idea how what you stated relates to Forbes’ median salary presentation.
Yes, they still require the algorithm course, but not the other theory courses.
What gave you that idea? I love the UC’s! While both kids had acceptances to them, and they were in the final running, both chose not to attend one.
You can always give me a hard time about CP SLO’s football team. Wow, they’re awful. During summer orientation, the football team was walking to practice (my dog was taking a pee on the lawn) and I think I was bigger than most of them and that’s really not saying much. Looked like they had a bunch of kickers and waterboys (water-persons?) on the team. 
Good luck to UCLA this year. Too bad they lost to Fresno State in the last seconds on Saturday night. But that was a great game, although FSU kept turning the ball over. One of D18’s very good friends plays for FSU. So, I was rooting for FSU.
To some extent this is variable. In my experience faculty at the UCs do a much better job of mentoring prospective MA/PhD students than the staff does of mentoring applicants to professional schools. Advising for major fellowships (Rhodes, Marshall, Churchill, Fulbright, etc.) is also decidedly lacking compared to the elite private colleges.
No comment about UMich against OSU?
And the turnovers were 3 for Fresno and 2 for UCLA.
Test Scores are under “Student Selectivity” in the USNWR methodology. If schools are not using the scores in selecting a material potion of the class then how do they reflect the school’s “selectivity”?
Also, the minute that a data set like SAT scores not only is self-reported with different standards from school to school, but includes a component where the schools are discouraging some students from providing the data, the “averages” and even the “ranges” are even more meaningless.
Absolutely! I suggested that if you’re interested in a Navy stint, why not get your education paid for at a very prestigious college and come out as an officer? My brother, who is an Army vet with four years tenure, thought that was too challenging. You have to get a congressional letter of recommendation.
It reminded me of another niece who graduated in the top 5% of her class in east Texas and had a single parent whose main job was driving a school bus. A TCU admissions officer was a grad of her high school and highly encouraged her to apply. She and a friend laughed that that was ridiculous. The cost is silly high. In October of her senior year, I told her that I would pay for her to apply to UT-Austin where she’d have auto admission. She declined the offer because she said she’d already been admitted to the local community college. That is just a window into how hard it is to attract students needing significant financial aid when more colleges are going after Pell Grant students, in particular, to boost US News stats.
Jim Harbaugh appears to be STILL stuck in a time warp back to 1905, before the forward pass was legalized.
Maybe the probability of a win against OSU has increased ever so slightly, because the game will be played at the Big House and OSU is still figuring things out. But talent is talent. And OSU has more of it.
I got it the first time you mentioned it.
Ah yes, the inference. That which we are free to draw from a submission of objective data or facts. But context in which that data is offered can also be relevant to the inference. Maybe a trip in the time machine would help us sort this.
I questioned the assertion that rankings services cherry pick what they include or ignore to serve their bias for elite privates. Beyond questioning the accuracy of that charge, I suggested it might make sense to not use Big Sport U’s recruiting numbers against them, whereas it doesn’t make sense to exclude that data for an elite small private college for reasons I mistakenly assumed were obvious. Surely, though, you agree that even Wesleyan’s recruiting is quite different than Alabama’s.
That poster never responded to me, but you did by taking me to the CDS data field and pointing out that some of these small colleges admit a very small percent from the bottom half of the HS class. A blunt chunk of data, for reasons that also should be obvious in the context of my post, but so be it.
So now we’re back to your reference. To what end? Is it to encourage me to draw the right inference? Wesleyan takes more kids from outside the top 10th? Everybody knows that Wesleyan takes chances on kids that Hamilton or Amherst probably wouldn’t, and there are a variety of reasons for why they do. They could do otherwise; they certainly get enough applications. But that is another thread. My point here is that even Berkeley’s CDS will likely show some surprisingly low numbers, and athletic recruiting at that level is often the source.
I apologize if I’m off target. If I am, then I don’t get the point. How does this matter relative to the point that there are really great academic public universities that also have big sports programs, and some of their outlier stats reflect that reality?
You are misunderstanding.
USNWR is using full data sets of test scores, at least for the schools that have all matriculants report test scores, whether or not they applied with tests. That data is what the CDSs show, and what the colleges report to USNWR…Matriculated student data NOT admitted student data.
If schools don’t have all matriculants send in scores, then yes, the CDS would not reflect full data sets. This year’s selectivity methodology penalizes schools that don’t report full data sets of test scores if greater than 50% of matriculated students never submitted them.
If you don’t believe Forbes is being truthful about the methodology they use, then why bother with the ranking at all? Suppose Forbes was lying about saying they weight CS and Payscale salary equally in their methodology. What would be the purpose of that lie?
I believe Forbes is being truthful about using CS salary in their methodology for computing rankings, so accuracy and meaningfulness of CS salary is relevant to Forbes ranking.
Which may be why Cal Poly SLO, a regional university in the USNWR rankings, is ranked #58 in the Forbes ranking. As one example.
I think that all adds up to “we’re in agreement,” although I wasn’t really a part of the Harvard/Westlake discussions. I’m not the one who brought up class rank in the first instance. At least I don’t think I did.
I believe USNWR classifies Cal Poly SLO as “regional” because they offer few if any PhD programs. This “regional” label should not imply Cal Poly is ranked worse than all of the hundreds of “national” universities with PhD programs. That said, yes salary based rankings tend to favor colleges with a large portion of the student body pursuing majors and career fields associated with a higher salary, like Cal Poly.
If you don’t believe Forbes is being truthful about the methodology they use, then why bother with the ranking at all? Suppose Forbes was lying about saying they weight CS and Payscale salary equally in their methodology. What would be the purpose of that lie?
You’d have to re-read my initial post on the matter; #277. I was just asking @tsbna44 about his link showing the Forbes’ Rankings. I guessed that its rankings used Payscale because the medians look like theirs, and I cited the error in taking these as truth. You chose to counter a small section of my post and to ignore everything else I stated to tell me that it also includes College Scoreboard – but don’t get me wrong that doesn’t disturb me in the least. My problem is your constant argumentative mode, probably remnants of our run-ins in the past – if you don’t remember as on the UC board.
Again, the problem with using Payscale is that it eliminates all who have grad degrees, so for the majority of top-tier colleges, Payscale eliminates > 50% of a college’s baccalaureate degree holders from salary data. And even for non-elite top-tier publics like UCLA and UCB, a good 65% of their BA/BS degree holders attend grad school, with UCLA’s being the most preprofessional of all the UCs. There’s also problems with sample sizing, and I’m not sure if this is what you intimated before, because I really didn’t follow your point about adequate sample sizing, other than the more the better. But though PS has a lot of database information, it’s a voluntary participatory survey and it’d be hard to obtain the correct mix of majors/perusals to calculate a correct median salary for a college including by eliminating those with grad degrees by passive survey-taking.
Re, College Scoreboard, it’s just one economically based demographic from each of these colleges. It’s a very important presentation, but this demographic applies to what, 1/5 of some universities? Additionally, it presents things by major/perusal, so there’s a problem of also of getting the right mix of them to present a median salary. Therefore, I don’t see how a median from all these disparate majors can be derived.
And I’m saying now for the third time that there are some colleges in which the median salary information is pegged incorrectly and is quite obvious. I listed some of them just previous to this post.
Since PS has been presenting college median salaries for awhile now, it’s evident to me that Forbes is just using PS’s data for each college. As it says, to which I completely agree, there is no perfect median salary predictor.
And yet you did that very thing in this post:
So, you were comfortable giving the benefit of the doubt to Williams’ 1% because of the 99%, even though Williams is known to place a great deal of importance on athletic excellence. That seems like an opinion to me. You also at least implied that the schools with a lesser % in the top quartile should be more open to inquiry with respect to their 1%, 2%, 3% or whatever it is. In fact, it was you who started this line of discussion (with me) referencing the latter group of schools solely to make the point that there are likely some low stats admits there (otherwise, your post served no purpose). And again, another opinion.
So a poster (whose username ironically is Data10) comes along and points out the limitations of using data sets (class rank) that rarely exceed 30% of the whole, and (IMO) cogently proffered good reasons to draw a few “inferences” from the missing data. One such inference might well suggest that the Williams 99% might not hold up if the missing 70% were to see the light of day. In fact, that 1% might go up a click or two. This seems straight-forward: CDS class rank is a bit of a clumsy and imprecise data source. And now all of a sudden opinion and drawing of inference is not ok.
I’m sorry, but you seem to be cherry picking here.
Seems that, in recent years, 43% of college students received federal grants, and 44% received federal student loans. Obviously, some students received both, but that seems to be hard to find (so it is hard to know what percentage received any federal financial aid).
However, the percentages are lower at elite private schools.
Your post 277 stated, “Is Payscale (“PS”), from which Forbes cites median salaries for each of its ranked colleges, still only using baccalaureate degree holders for its salary reporting? They weigh this variable at 20%, which is pretty significant.”
You implied Forbes’ ranking weights Payscale salary at 20%. I replied saying that the 20% salary weighting you mentioned was computed from half (10%) CS salary and half (10%) Payscale salary, rather than all (20%) Payscale. I see no further reason to rehash the previous comments from many dozens of posts earlier , but if you read each of my replies, it should be clear what I was replying to and how I came to the conclusion, and the later posts did reply to the bulk of content in your posts. However, the later replies were not talking about comments in post #277. They were talking about the comments quoted in that reply.
You’ve made personal and negative comments like this multiple times in this thread, perhaps because of this r past history from comments made years ago on the UC board that I do not remember you mention. If you do this and/or call me out specifically, do not be surprised if I reply and/or disagree with the comment.
My post said, “If you compare CS salary to salaries reported to the college as whole through student surveys, you’ll generally find they are similar when sample size is significant. The bigger issue in my opinion is sample size is often not significant, particularly in smaller majors.”
I was talking about CS salary, not Payscale salary. CS salary sample size can be small, particularly in smaller majors. For example, suppose the sample group for English majors was 10 students. That salary median would be expected to have a wide possible range. There may be large variation from one year to the next, with such a small sample. In contrast, if sample size was 200 students, the salary median is expected to have a much greater precision. CS tells you the sample size (if I remember correctly, they also list SD in the raw data files), so a person manually reviewing can estimate precision and possible range. However, just using the number in isolation without considering sample size like Forbes does, is more problematic.
CS presents the median by major as well as overall. A user can consider either or both. I personally find it meaningful to control for major when comparing salary, so a prospecitive mechanical engineering major can compare median salary for mechanical engineering majors at college A to median salary for mechanical engineering majors at college B… rather than comparing the median overall salary at college A that is composed of mostly tech majors to the median overall salary at college B with that is composed of mostly humanities majors. I believe Forbes does not control for majors in their rankings.
I at least agree with this part.
This will certainly be an issue next year. The current data, using 2019 admissions, not so much.
NYU’s 1540 “average” illustrates the issues CDS reports will have starting in a few months. USNews and others will need to significantly adjust.
Having had kids recently graduate from both UCSB and UCLA, I’ll chime in. Until the pandemic, housing at UCSB was one of its best features. Students were guaranteed 2 years in the dorms and then 2 in the apartments. Four years of guaranteed housing was fantastic. Getting classes, at least for an engineering major, was no problem because if you needed one to stay in sequence, the department would get you in. UCLA had the next best housing guarantee in the UC system with 3 years guaranteed. The Hill, where the students live on campus, is a great environment. Getting classes there wasn’t an issue either because so many are offered multiple times a year, at least for engineering. Our son would see some complaint online about getting classes and shake his head because it wasn’t his experience at all. He often had 16-18 units, so it wasn’t like he was struggling to round up 12 units. UCLA also offered some great research opportunities for undergrads. I don’t doubt there are issues this year or last because of pandemic-related problems, but our experience with those 2 schools was overwhelmingly positive.