@eyemgh I gave enrollment numbers not yield, the actual number who enrolled, as I said they do not give us the number accepted. But when you said single digit acceptances, I pointed out that enrollment was too high for them to accept only a single digit percent of applications. Everyone has access to enrollment figures for each major, they are on the projections.
Totally agree about the strength of the applicant pool by major. Psych is a difficult to get in major based on the number of applicants and the spots open, however the average applicant for Liberal Arts is lower than the average applicant for engineering. That is why I say it is important to look at the average and in a tough major expect to be higher than the average by a decent number. I wish CP provided 75th percentile numbers even for each school but they do not, there is an overall 75th percentile test score number in the Common Data Set, but that is it.
@eyemgh using averages by college is more accurate than using overall averages and for engineering for example as most majors are pretty difficult and those that are easier are such a small percent of the number of applicants so it won’t be as variable as say CSM or Ag/CAFES. I prefer to give the averages AND the comparative difficulty of the major for example, in engineering if someone asked for CS, I would respond you need nearly perfect GPA and near 1500 test scores just to get accepted in engineering as that is the average for the students accepted in 2017, and CS is likely even more competitive than that.
We also know they accepted around 26% of the applicants in engineering and based on projections expected about 26% of those to enroll. But if you use those percents for Computer Science, for example, it would result in more than twice the number of students they want to enroll. It is obvious using those numbers for individual majors doesn’t work well. Using the GPA/test scores seems more reasonable, plus of course taking the additional math and science recommended courses, seems more helpful and more accurate. But when you add in variables like OOS students tend to have slightly lower stats, and there are some admitted using the non MCA bonus points some students have a chance to get in with lower stats. There are so many variables, and we are working with an MCA system we last have info on from 2011, and that is from a senior project that I know there are errors in, the last CP information is from 2009 I believe. You can do a public records act request to get information on individual majors and probably mca scores, as it should be public information.
I just know when mine applied making sure his stats were well above the average for his college (CSM), and test scores were above the 75th percentile, that he had all the course difficulty points, and maxxed his GPA worked. That is what I suggest to people wanting to get in the very competitive majors, and it has generally been accurate. Only one student I thought would get in, didn’t, and it turned out he didn’t include his courses in middle school, so it appeared he didn’t meet all the requirements. Most highly competitive majors are a toss up, CS for example, as it is as competitive as a top UC to get in, but without the course difficulty points, I’m not sure even perfect GPA and test scores will get you in.
@czs1994, your numbers don’t make any sense. Let’s focus on 2016 CS. CP projected 4057 applicants and enrolled 102. Please explain how it’s not possible that the acceptance rate was below 10% for CS. Even if yield was only 25% for CS, which I highly doubt, the acceptance rate would have been right at 10%. Any yield higher than 25% would mean the acceptance rate was below 25%.
@eyemgh and @Gumbymom thank you for all you do on this forum. And I have to agree strongly that looking at the CENG overall acceptance rate is not helpful in determining ones chances for acceptance for individual CENG majors.
As an example the highest rated applicant to IE last year would barely have been admitted to ME and would have been rejected from CS. The number of applicants AND the strength of the applicant pools are very different for each major in CENG. I base this conclusion on actual knowledge of the MCAs of several students who applied last year and reviewing the MCAs reported on this forum.
It is helpful for applicants to know CS is in a world of its own as far as competitiveness. I mentioned this in a previous forum, but I know a student accepted early decision to Stanford that was rejected to CS and similar stories for students accepted to Harvey Mudd, MIT, and the Ivies. Looking at the overall acceptance rate and admissions stats for the CENG as a whole would be extremely misleading for a CS applicant.
It is also helpful for applicants to realize the next group- BME, AERO, ME and perhaps surprisingly ENVIRO are extremely competitive and much more difficult to gain admission compared to EE and GENE and it even the closely related CIVIL.
Why more students do not apply to GENE is beyond me. It is a fairly easy admit and it is the one CENG major that allows you to transfer to any other CENG major with minimal GPA requirements. It is in fact designed for students to transfer from.
Once again thanks to @eyemgh and @Gumbymom for your years of service to this forum.
@eyemgh I definitely would agree that the acceptance rate for CS could be 10% but is likely more like 13-15%, we know the overall rate is around 21% (and I would disagree that the enrollment rate would be higher than the average as they underenrolled in 2016 by over 30%, which brings up my point that you should use the projected number of students they strived for not the number who enrolled as that is what they use to figure the number they accept, that was 141 which divided by the number of applications of 4057 gives you 3.5% divided by the overall acceptance average of the prior 3 years of 22.6%, you end up with a 15% acceptance rate. (2017 they totally messed up, accepting way too many students with a normal yield).
My points are two fold. One, we have facts for each school as to acceptance rates, so rather than using the same formula for every major, you can, and imo should, use real numbers as much as possible. The “system” works fairly well for Engineering, but is way off for other majors. We also know which majors are the most competitive so again imo, we should respond to questions, should we decide to give advice, with as accurate information as we can, which involves using real acceptance rates adjusting for whether it it is a relatively easier to get in department or a crap shoot like CS.
Second, telling someone you have a 10% chance of getting in is really meaningless. Someone with a 3.0 gpa and 1100 SAT has no where near a 10% chance which is where average gpas and test scores can be more helpful. Someone who meets the average gpa and test scores may have a 10% chance. If your scores are higher than that you probably have a better chance while not meeting those makes it a definite reach. It is also important to know that even if you have the max 4.2 gpa and a 1550 SAT your odds are likely much lower if you don’t have the 2 years of additional math and lab science for the tough majors, and likely for the STEM majors where many/most of the applicants are likely to have at least some additional math and science over and above the minimum requirements.
I respectfully disagree. The standard deviation of acceptance rate is so high within the CENG that it renders the mean meaningless.
What you sat about selectivity is true.The selectivity of a major tells us one thing and one thing only, how popular it is. Everything that IS important can be boiled down into one metric, MCA score. It factors in all the things Cal Poly cares about, both academic and non-academic. That’s why I always advocate students (or parents) calculate their MCA score and compare it to the posted results from the last few years. It’s imperfect, as far to many posters accepted and rejected only post classic stats like GPA and test scores. For all we know, it may have changed. What I can say is that I’ve yet to run across another school where I have as solid a handle on projecting admissions as we do at Cal Poly.
@eyemgh “The standard deviation of acceptance rate is so high within the CENG that it renders the mean meaningless.” Where do you get this information? I would love to see the different acceptance rates, I doubt the larger majors which account for the vast majority of the department and applicant pool, vary all that much. I don’t suggest saying all are equally difficult to get it, I do say to point out if a major is going to be harder or relatively easier than the average.
MCA is a great system in my opinion, and when students calculate their score properly it does give them some idea. You also only have extremely limited numbers and majors covered. It is helpful for a few, and for those truly having a 4700 first run score their odds are pretty good for most majors. However from reading posts for years few people calculate it properly. How many people say their gpa is over 4.25 (there is some question whether 4.2 is right or 4.25 which is mentioned in a WASC accreditation report)? How many miscalculate their course difficulty points and use 900 or use courses that don’t count? So many assume the second run with the extra points goes into the MCA and always counts. First they need to meet the minimum cut off to apply to the department to make it to the second run, and second there are only so many spots for the second run, they need both scores. I looked at all the complaints after acceptances come through and gave up. You have a lot more patience than me. We don’t disagree on the benefit of the MCA and properly calculating it, it worked for us. We disagree on using the same calculation for all majors to tell students acceptance rates for majors.
@eyemgh, you confused me when you called it the acceptance rate, I always use those numbers to try to figure out acceptance rates but it is a guess. I don’t see the disturbingly high deviation of enrollment rates that you do. Overall it is 7%. Only Industrial, mfg, and materials are at or above 20% and they account for 10% of the enrolled students. Electrical, 13% of estimated students, is around 17%. The remaining 75% of the enrolled students had rates of 4-11%. There is a much bigger variance in other colleges, and the overall enrollment rates go from 7% to 19% which is why I don’t like using a single number for each college, much less major.
@czs1994, I get my data straight from Cal Poly’s Institutional Research page. The bottom line is this, in the least selective major in the CENG, manufacturing, almost everyone who applies gets in (2017 Projections, 67 applicants for 22 slots, assumes 33% yield), but in the most selective major, CS, very few get in (2017 Projections, 4377 applicants for 130 slots, assumes 33% yield). Between those two, we have a nice distribution of the rest of the majors, skewed a bit toward the more selective side. (Note: we can’t really use actuals, because they don’t post the actual number of applicants by major, hence projections.)
If you want to back up and restart this, please don’t simply supply the final number of the calculations you made, but the actual source numbers and where you found them. As it stands, I can’t replicate any of your calculations from Cal Poly published data.
If you prefer not to rehash, as my son would say, I’m down with that.
@czs1994 Your discussion of acceptance rates is very confusing. @eyemgh has done years of work on this board to bring clarity to Cal Poly’s admissions. Your critique of his methodology is hard to follow and I fear is hurting rather than helping students assess their chances for various majors in the CENG.
Source: I am a parent of four Cal Poly CENG admits (ME, BME, EE, and IE). I have also followed several other students through this process.
I think we figured it out. @czs1994 thought we were using 33% as the admission rate for all majors across the board. As you know, 33% is the typical yield rate across the whole university. That’s where that number comes from. Were we actually saying that, I could understand why someone would want to correct it.
@choroidal sorry you are confused, it isn’t too hard. Basically acceptance rates by college vary from 23% to 43% and yields range from 21% to 47% so I do not agree with using one number for all colleges.
Acceptance rates overall, and by college are easily attainable using this for 2016 https://content-calpoly-edu.s3.amazonaws.com/ir/1/images/Fall%202016%20Admissions%20InfoBrief.pdf Essentially his method uses the same acceptance rate for each college, and works well for CENG, it however does not work well for the colleges with acceptance rates significantly different from Engineering. Since the math involved and the number of colleges and majors, I took our discussion private so you wouldn’t continue to be confused.
Obviously use what you are comfortable with, luckily yours are all in engineering so it didn’t matter for you.
Your’re making way more of the “real” numbers than can be substantiated. Since we do not know actual applicants per major or yield per major, making the calculation more complex by using actuals only for students admitted but not taking into account for actuals that applied, and using yield per college, but not yield per major MIGHT make the calculation SLIGHTLY more accurate, but it could just as likely, since WE DO NOT KNOW THE NUMBERS, make it slightly LESS accurate. The bottom line is this, by using PROJECTIONS to make a reasonable guess at selectivity and comparing calculated MCAs to previously admitted and rejected MCAs, perspective students have as good a prospect as is possible to gauge their chances.
@eyemgh no I know the calculation suggested on these boards does use a 33% admission rate across all majors and colleges. When you suggest dividing the number of students projected by the number of applicants (an absolute yield) before using the x3 or /.333 (same mathematically) the x3 is an admission rate (of 1/3 of 33%), that you DO use across the board.
33.3% is close enough for Engineering and Business, but under estimates chances for CSM and to some extent LA, and way over states for CAFES and Architecture. Admission rates run from 23% to 43% and yield rates run from 21% to 47%, I suggest using your method for yield but actual numbers for admission rates. The rates can be found here https://content-calpoly-edu.s3.amazonaws.com/ir/1/images/Fall%202016%20Admissions%20InfoBrief.pdf
A properly calculated MCA together with average GPAs and test scores is better anyway, was just trying to improve the calculation when someone tells them to use a 33% acceptance rate across the board since we know the actuals by college.
The 33% is not acceptance rate. It is yield. To use the yields from the respective colleges makes the calculation more complex and may make the result more accurate. Since we do not know yield by major it is just as likely that using yields by individual college results in a LESS accurate result. That, and simplicity, are why I and I presume others, use 33% YIELD. The whole conversation has been a Tempest in a Teapot. Whether you use your method or the simpler one I advocate, it’s at best a guess.
@czs1994 Late reply, sorry. I think @eyemgh covered my concerns.
As an aside just 2 of my kids are in engineering. The 2 others chose not attend to Cal Poly and graduated elsewhere. But, the discussion still matters to me. My kids received useful info on this board when applying and thus I feel an obligation to those applying now to make sure information is presented clearly.
My daughter just received her acceptance email from Cal Poly SLO in environmental engineering! I’m so proud of her! She is so excited since this was her top choice!
My son is a junior and, sadly, has to already start making tough college planning decisions. I wish the process was more scientific with predictable outcomes! Here is what I am struggling with and would be so grateful for input and shared thoughts.
I predict Cal Poly will be his #1 choice so he should go “all in” which means:
a) A 5th year of English even though he is max rigor MCA points. Admissions recommends it and won’t endorse the old MCA rigor assumptions. Any advice on where to get a transferable online English course? It has to be online because his course load is full and he is attending the UCLA Applications of Nanoscience this summer.
b) He might be a little shy of the 21+ Work or internship hours. How exactly does that application word this section? If he applies 10/1 does he need 21 x 52 weeks (1092 total hours) for the preceding 52 week period?
c) If I’m doing the MCA calculations correctly, every full letter grade only makes a difference of 15 points. Presently, there is an odd Honors PreCalculus course thing going on and he received his first C last semester. He is set for a C this semester without dramatic intervention (private tutoring, time dedication). Not sure he wants to do that to maybe get a B or just eat the 15 points and make sure the rest of his courses stay at As. He is already max 8 semesters weighted and should be at a 4.05 even with that darn C.
FYI: His SAT is a 1580 putting his MCA at about 4900 +|- 15 for a grade variation so his chances are good.
d). Is Computer Science or Computer Engineering less competitive? Any other majors that are reasonably similar and less competitive to look into?
Other schools
We will look at Mines and Purdue but I think he wants to stay in CA. I suppose he will throw his name in the UCSC hat if I can get like 12 essays out of him! So, mainly his other schools will be UCs and the only issue with those that I’m struggling with is the recommended SAT science subject matter test. He only took basic biology and chemistry. He is currently in Honors Physics with an A+ and plans to take AP Physics next year. I hear the physics test is a nightmare. Could it actually hurt him? Any suggestions? It’s UCSD, UCLA and UCD (too I think) that “recommend” (code for require) this. I don’t want to spend too much time on this when he wants to go to SLO but would it would be foolish to not plan for contingencies. Who knows? He might fall in love with UCLA this summer. My gut tells me to spend his time getting the work/internship hours for Cal Poly.
Thanks in advance for help with these technical questions. The process really requires knowledge and advance planning - a little too sophisticated in my opinion for a high school junior.