kingduck
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Posts posted by kingduck
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May I ask, where else have you heard back from, and which others you are applying to? I am in the current biostats application cycle as well, but for the Fall 2021 cohort.
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Thanks @kingsdead and @cyberwulf, for the peace of mind.
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I was just made aware that a biostat department had not received my official GRE scores yet, which I ordered last month. The deadline was 12/1, and I checked SOPHAS, which indicated scores were posted today 12/8. Assuming that the scores did go through, am I already considered a late applicant because ETS didn't send scores in their mentioned 5 business days? When do departments typically start reviewing applications? UC Berkeley says material must all arrive by 12/18 despite the deadline of 12/1, so I'm hoping that's the case for other schools too...
How ETS sends the score reports is out of my control, but will I be penalized for this?
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I am applying for biostats programs, and I was wondering how interviews are notified. That is, if we are notified of a decision before an interview is scheduled, does that imply the decision is a rejection? Or have programs that typically interview, accepted candidates without interviewing?
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I initially thought I'd have trouble securing three faculty members for strong letters, so I contacted a fourth. This professor was very enthusiastic and offered to write after I sent her some of my application material like deadlines and SOPs. Well, my three letter writers came through, third one submitted almost half of his letters, and committed to finishing the rest of them.
Should I keep fourth writer in the loop, in case my final recommender doesn't finish all of them? If not, what is the best way to tell them that I don't need anymore letters? Normally, I'd just submit all 4 letters, but many programs only want no more than 3. I could say that my final recommender who hasn't finished all the letters yet, would write me a much stronger letter.
I don't mean to sound unappreciative or as if I am using these professors, but I do want to make sure that I don't burn bridges while also having the best letters I can get.
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I had recently submitted my SOPHAS application.
A couple weeks ago, I made the request for my transcripts to be be sent from an institution, but it is taking a while for the registrar to process the information. Additionally, I had ordered my GRE scores, but I have no guarantee they will make it in time for my December 1st deadlines. My question is, how do departments evaluate SOPHAS material that come in later? Will I be penalized for the delay in the getting some of the supporting documents in, or am I ok so long as it has been postmarked before the deadline? My SOPHAS applications are showing as received but no verification yet. I'm assuming it would only happen on a business day.
I have never used SOPHAS before, so this has been quite hectic for me.
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@cyberwulf what is the marginal benefit gained from going from 165 to 166? Is there a threshold before an application is auto-rejected, or is there a range of scores in which adcoms determine to be acceptable scores?
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I was working on my CV, and in my work experience section, which was listed at the very bottom, I wrote something along the lines of "researched x,y,z to asses the viability of... etc." It's clear that I meant to write "assess" as a verb and not the plural of "@$$". Obviously, I missed it the first time I proofread my CV, and so did my recommender who went over it with me. I would consider this a small typo in normal circumstances, but this is a swear word.
I'm hoping the adcoms will overlook it too, as it sounds like they really only glance over CV's, let alone the work experience section. I do have a research and papers sections listed higher up on the CV.
Any chance this will ruin my app? I caught this error after only submitting to 1 school. So other schools will be getting a more thoroughly proofread document, without swearwords in it.
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I had an almost similar profile to you. My major GPA (econ) and gen eds are what significantly lowered my GPA. I'm in the application process right now so take my advice with a grain of salt.
1) From what I've noticed, for the masters, adcoms care a lot about linear algebra, multivariate calc, and some sort of calculus based probability. Since Dec 2021 is still a year away, so you might want to retake a more advanced version of those courses, maybe linear alg and probability at the graduate level - and really any course that you might think will cause adcoms to question your mathematical ability. Retaking the courses and doing well will compensate a bit for your lower lin alg, econ stat, and psych stat grades. Also the GRE Q will be important. Try to get as high as you can; 165+ is a good goal to have.
2) As for schools in CA, I would also add CSU East Bay. I work with several brilliant data scientists and statisticians who got their MS in Stats from there. As I'm in the application process, I am not confident of my ability to suggest some more appropriate schools.
3) I believe quite a few reputable members on this forum have mentioned in other threads, that going for a stat masters would be better for a PhD down the line, if the master's coursework is rigorous. As for applied stats, you might want to consider certain online programs or business schools that offer the applied stats MS, and I believe Santa Clara University is one of those schools (not 100% sure). It's my impression that applied stats usually isn't as rigorous as traditional statistics degrees, but in the industry, I don't think it makes much of a difference. However, I do think the math grades are what will hurt you the most in getting into a PhD program in the future, and the lack of Real Analysis.
4) Maybe also add CSU East Bay and Santa Clara. Since you already have SJSU in the list, might as well add a few schools in the area as well.
Again, my advice is just from what I've observed from lurking around here, and from talking to professors about my background. I hope I'm not spreading fake news here. YMMV, good luck.
- bruinlookdown and iggygc
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I have an MS in stats, but I don't have much YOE, so my experience is based on my observations of my colleagues, and my experience may not be applicable to your situation. Several of my colleagues had business degrees or social science degrees, who ended up wanting a career change into something more technical. The more technical folks got an MS in stats, while the less technically trained folks, went for a more professional MS, like in applied analytics or masters of the sort.
They were able to land a job in a more technical space, but some had down-levelled because they had no professional experience in their new field. E.g. I knew a director who went from senior associate business intelligence (5+ YOE), and down-levelled to data analyst (normally 1 YOE folks are here) at another company, as his BI experience was basically negotiating contracts with data vendors. Despite his dual master's in international business and MBA, since he ad little professional experience in analytics aside from his newest degree, he had to make the choice to start over again. However, I think he would have no problem being promoted quickly given his professionalism and YOE. On the other hand, I had a coworker who was promoted as soon as he earned his MS in analytics part-time, since he was working in a technical capacity already.
I was able to switch into an R&D role as a data scientist with my masters in statistics. I was a BI analyst prior to that, but my work was fairly technical. I would presume with enough experience, you could get promoted eventually, however I think I was up-levelled sooner, at least partially due to my MS. So it seems the question really comes down to how you showcase the skills you bring to the table, and at the root of it, what your goals for getting the master's are. In my experience, the MS was worth it, but if I was at a much senior level today, I don't know if I could say the same, as my career goals would likely be different.
btw, I saw your previous post about low GPA. I was admitted to a decently ranked program with a 3.3 ugrad GPA.
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I am currently converting my professional resume into an academic CV (for biostat applications), which involves deleting certain skills that are only valued in the industry, and adding certain things that are valued in academia. Currently, in order, I have the sections:
1. Summary and Objective - brief TLDR of my SOP, 3 sentences
2. Education - no GPAs listed, should I? since they'll be getting my transcripts anyways...
3. Research - 3 research projects, unfortunately no publications resulted
4. Skills - I have a few coding languages in here, I used to have things like SQL, AWS, Hadoop but unsure if that is going to help my CV
5. Professional Exp - over 1 year of working on interesting stats projects in R&D at companies
6. Relevant Coursework with relevant coursework GPA listed - I come from a non math/stat background for ugrad and received a stats masters
7. References - same as recommenders for my apps
It is about 1.5 pages long written in LaTeX. Given that the pinned post by @cyberwulf does not contain any discussion on CV, I'm assuming that is like the SOP; as long as everything checks out, it doesn't really improve or hurt chances. Are there any red flags that I should be sure to avoid, or anything that might be raise the reviewers eyebrows?Any advice is much appreciated.
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@HighStat I found this out on chronicle of higher education. Article is here:
https://www.chronicle.com/article/more-doctoral-programs-suspend-admissions-that-could-have-lasting-effects-on-graduate-education?cid=gen_sign_in (scroll to where it shows a table of suspended programs)
And an article from someone I'm in a groupchat with:
https://www.outlookindia.com/website/story/opinion-what-is-the-future-of-the-american-phd/361192 (second paragraph last sentence)
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In light of many schools announcing suspensions in their application cycles, like Columbia's statistics program, what are your plans for applications, should more programs in other schools be suspended?
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Hi guys, this is about LOR strategy in the math/stat space, and I thought it might be helpful to have my profile attached as well. I wanted to know what the best strategies for getting letters of recommendations are. While I have been through the LOR process for the masters applications, I wanted to take a more nuanced approach this cycle.
As mentioned previously, I have 1 professor (call him professor X) from my masters program with whom I took 2 classes with and we are currently working on 2 research topics, one on time series and one on COVID data analysis. Another professor (call him professor Y), I have also taken 2 classes with: in mathematical stats and survival analysis. I am hoping to receive good letters from them, but what should I ask them to emphasize on (or what is an appropriate way to ask them to talk about my research/math ability)?
My plan is the following:
- Professor X: ask to speak to my research ability
- Professor Y: ask to speak to my mathematical stats ability - i have discussed with him some research methodology (regarding the work with professor X) but not extensively
I have three more professors I am considering, a marketing professor from my undergrad with whom I did some text analysis with (call him Professor Q, and wrote my letter for my masters application), a stats professor from my grad program with whom I got an A in his multivariate stats class (call him professor R), and my real analysis professor (call him Professor S, who is a math lecturer at Harvard).
- Professor Q: really nice guy, think he will write a letter that speaks to research and data analysis ability, like he did before
- Professor R: unsure - I also spoke a little about potential research in multivariate stats with him (nothing became of it), probably an average recommendation along the lines of "good at linear algebra/math"
- Professor S: lecturer at Harvard, found one of his letters online and seemed to be rather uninformative (student scored 98% on exam 1 etc..., we covered materials XYZ from textbook by Professor so and so.)
My questions really can be summed up as the following:
- What type of letters should I aim for? Should they say how good of a student I am, or how good of a researcher I am?
- Should I even consider professors R or S, since their letters are anticipated to be pretty average?
- It seems like a no-brainer, that I should ask professor Q, since he can speak to my research ability, but will the fact that he's from the marketing department somehow make what he has to say about me weigh a little "less?"
- What is the most appropriate way to ask a professor to write about, say, research ability, or math ability?
I'd appreciate any advice on LOR strategy
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I'm in a similar boat, struggled with what I wanted for a career (hence had a low GPA), discovered math and stat as part of my degree and went on to a masters. Wanted to see if anyone else had insights on how to explain such a change in GPA and career path in the SOP, or maybe even from the recommender.
I've lurked around on the forums and am also in the application cycle, so don't consider what I say as expert opinion. For a biostat program, it seems you have the requisite math courses and scored well, though you might want to have more stats. It's my understanding that UC Berkeley requires a masters in biostats before their PhD, but I may be mistaken (check on their website). I've also been told that JHU and Harvard are quite theoretical biostat departments, so the lack of math further advanced math courses may not be helpful. However, you do have significant research experience, which adcoms may view favorably.
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Hi guys, unsure whether or not to start a new topic since this is about LOR strategy, and I thought it might be helpful to have my profile attached as well. I wanted to know what the best strategies for getting letters of recommendations are. While I have been through the LOR process for the masters applications, I wanted to take a more nuanced approach this cycle.
As mentioned previously, I have 1 professor (call him professor X) from my masters program with whom I took 2 classes with and we are currently working on 2 research topics, one on time series and one on COVID data analysis. Another professor (call him professor Y), I have also taken 2 classes with: in mathematical stats and survival analysis. I am hoping to receive good letters from them, but what should I ask them to emphasize on (or what is an appropriate way to ask them to talk about my research/math ability)?
My plan is the following:
- Professor X: ask to speak to my research ability
- Professor Y: ask to speak to my mathematical stats ability - i have discussed with him some research methodology (regarding the work with professor X) but not extensively
I have three more professors I am considering, a marketing professor from my undergrad with whom I did some text analysis with (call him Professor Q, and wrote my letter for my masters application), a stats professor from my grad program with whom I got an A in his multivariate stats class (call him professor R), and my real analysis professor (call him Professor S, who is a math lecturer at Harvard).
- Professor Q: really nice guy, think he will write a letter that speaks to research and data analysis ability, like he did before
- Professor R: unsure - I also spoke a little about potential research in multivariate stats with him (nothing became of it), probably an average recommendation along the lines of "good at linear algebra/math"
- Professor S: lecturer at Harvard, found one of his letters online https://www.theodorecaputi.com/files/Math23ALetter.pdf which does not seem to be a strong one (correct me if my assessment is wrong).
My questions really can be summed up as the following:
- What type of letters should I aim for? Should they say how good of a student I am, or how good of a researcher I am?
- Should I even consider professors R or S, since their letters are anticipated to be pretty average?
- It seems like a no-brainer, that I should ask professor Q, since he can speak to my research ability, but will the fact that he's from the marketing department somehow make what he has to say about me weigh a little "less?"
- What is the most appropriate way to ask a professor to write about, say, research ability, or math ability?
PS: checked my transcript, I actually had an A in real analysis 1, not an A-, not sure if that makes a difference at all at this point, and my GREs are Q166 V159 W4.0.
I'd appreciate any advice on LOR strategy, or any profile evals for those coming to this thread for the first time.
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14 hours ago, DanielWarlock said:
6. Upenn
AFAIK, Upenn does not have a terminal masters degree program in stat, and is earned on the way to a PhD, not necessarily a PhD in the stat department. That is unless you're talking about an MBA with a concentration in stat, which then has a different set of requirements different from an MS in stat.
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What do people think of Harvard's math 23-A for real analysis I going into a PhD program?
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On 5/24/2020 at 12:22 PM, StatsG0d said:
Calc I-III and linear algebra
Would AP'ing out of Calc I with a 5 score in high school be considered an A in Calc I when applying?
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11 hours ago, Casorati said:
You have good math grades from a top school and if you can improve your GRE Q to 166+, you should be able to get into some top 20s
@Casorati You know what, I just reviewed my ETS results for the GRE that I took 3 years ago, and I actually did score a 166 on the Quant. I had forgotten my score over the years lol. Now, my main concern is that my Verbal or AW score may be a bit on the lower side, or does the adcom really weigh in the V and AW scores as heavily?
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7 hours ago, Casorati said:
Admissions for biostatistics/OR is somewhat less competitive than statistics
1 hour ago, bayessays said:I'd apply to any biostat program and could see schools like Michigan as possibilities too
Thanks for the suggestions @Casorati and @bayessays.
I do worry that my background, not having anything related to medical sciences, may play against me in biostat applications. I have about 1-2 years of work experience in financial data analytics, (not quant finance, just quantitative strategy and market trend analysis using statistical techniques), but I am hoping to angle my research with the professor I am working with now, to a more health related application (in light of COVID 19 there are some studies that my professor is involved in). Without the experience in medical science, is it going to play against me?
PS: The research project I am working on is attempting detecting change points, which I am hoping to relate to applications to epidemiological models such as seasonal flu patterns.
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Thanks for your very helpful input!
I received my masters from an R1 public school, and does have a PhD program ranked in the 40-30 range on US News. I do think that my letters will hold some weight, and the professors I am seeking recommendation from have said I am an "excellent" student, so hopefully that will translate to good LORs. They each have h-indices of 20-25, but I'm not sure if that is a fair way to evaluate their "fame" so to speak.
I'm glad to hear that people with lower than A grades still make it to great programs.
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Hi all,
I am considering applying to statistics, IEOR, and biostat PhD programs. My interests are more in the methodological side of statistics, so OR and biostat departments may be more appealing to me (leaning towards biostat), but I'm not opposed to more theoretical stats. That said, I wanted to have more insight on what should be my reach, target, and safeties for PhD applications. I would also like to point out some problems in my transcript, and see what you guys may think about it. A bit about my profile:
Undergrad: Ivy League (not HYP)
Major: BA in Economics (Major GPA ~3.1, Overall GPA ~3.35) A few C's and several B's in Microeconomic-related courses, but A level in Econometrics, and Macroeconomics
Minor: Mathematics and Statistics (STEM GPA: 3.75)
GRE: (plan to retake)
Q: 164
V: 159
A: 4.0Graduate: Mid-tier state school
Major: MS in Statistics (GPA: 4.0)
Courses Taken (Undergrad Level): Multivariate Calculus (A), Diff Eq (A+), Linear Algebra (A), Probability (B+), Statistical Inference (B+), Mathematical Statistics (A-), Econometrics (B+), Advanced Econometrics (A), Data Mining (A), Statistical Computing (A), Time Series (A), Real Analysis I (A-), several CS related courses at the A/A- level.Courses Taken (Graduate Level): Probability (A), Statistical Inference (A), Survival Analysis (A), Linear Regression Analysis (A), Modern and Applied Statistical Modelling and Computing I and II (A), Time Series Analysis (A), Design of Experiments (A), Data Mining (A), Multivariate Analysis (A)
Research Experience: Had 2 research assistant positions in undergrad, doing applied statistics with business faculty. One independent study project in graduate school with a statistics professor (still in the works, trying to get published).
Problem courses (all undergrad classes in sophomore and junior year): Health Economics (C), International Finance (C), Literature in the 1900s (C), Accounting (C), Several B-level grades in gen ed courses related to social sciences and economics
I am worried about these problem courses since their grades are low. How will these seemingly unrelated courses affect my application in the stats, biostat, and IEOR fields? What schools should I be targeting? What schools should be safety? I am not even sure about the US News rankings, since there are mixed emotions about their ranking scheme. I plan on retaking the GRE to score a higher quant score of 165+.
Any advice and suggestions would be helpful. Thanks a lot.
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Thanks for the response. I have heard of several of these OR departments, and my only concern is that they may be heavily optimization focused, which doesn't line easily with my interests. My main interest in IEOR is the application of statistics, where there is a heavier emphasis on stat methodology. I think my research interest primarily lies within the methodologies rather than the mathematical theory, which is why FE appealed to me initially, given my econ background.
I've spoken to several faculty who mentioned the same as you, to broaden my scope, and to look into stat/biostat programs. I think my main concern is my Econ GPA, which was less than stellar, but I'm hoping my STEM courses can compensate for that. (I did end up finishing my masters with a 4.0).
Again, thanks for your input, and congratulations on accepting Cal's IEOR program. It is definitely hard to elicit a response on this forum for such hypothetical topics.
Best of luck in your studies! Maybe we will work together soon
MS in Stats to PhD ML via MSCS
in Computer Science
Posted
I typically lurk on the mathematics and statistics section of this website. I've been noticing recently that ML seems to be more housed in CS departments, while still drawing upon knowledge in stats, e.g. CMU's ML PhD has a couple courses on statistics as part of their curriculum.
The last two years, I worked in analytics while I earned an MS in Stats from a large state flagship, ranked USN top 50 in the field. I am contemplating on earning an online MSCS from UT Austin or GATech since I have always had an interest in programming and studying efficient algorithms. I have also taken a few into to CS courses, and I have had to code extensively at my job. Given my stats background, I am also interested in ML and the overlap between stats and CS. A couple programs that I've seen offer ML are GATech PhD in ML, CMU PhD ML, and Stats+ML in the UK (i forgot with universities were involved in this group).
I finished undergrad with a 3.3 in economics (low econ and gen ed grades, high STEM grades) at a top 20 USNR private school, and I finished my masters with a perfect GPA.
As the computer science field is very much new to me, is there any advice for me on performing doctorate level research ML? Would I have a chance at applying into CS departments that have a focus in ML? What is the consensus on the OMSCS approach?