Ask HN: Getting a math degree as a working adult? - <AUTHOR> My question: I've found a math degree to pursue, what (1st or 2nd hand experience-based) feedback can you provide as advice?
I am thinking of enrolling in this online BA in Mathematics program through Southern New Hampshire University: http://www.snhu.edu/mathematics-BA-online.asp
I'm a software engineer already working in the field I want to be in for the next 5-10 years (data logging and analysis).
I want to get a degree in math for a couple reasons: a) For me. I've always deep down wanted a degree but couldn't admit it to myself. I would for whatever reason regret it if I never earned a degree. b) When giving people advice around data I would like to train myself around many of the biases we are all so prone to. Learning though on the job in a business intelligence role seems like a very expensive feedback loop. (Imagine making a mistake in a recommendation that costs the company millions of dollars) c) I would like to eventually move into more machine learning and recognize that for now and the foreseeable future statistics and other math will play a HUGE role in that. For jobs in this realm a masters degree is very much encouraged.
Some background on me: My company and myself all work remotely so the discipline that an online degree requires isn't at all an issue for me. Also I am a self taught software engineer so I'm looking forward to taking whatever I learn through my courses and building on top of it as much as possible as I go.
Just to clarify my question is: I've found a math degree to pursue, what (1st or 2nd hand experience-based) feedback can you provide as advice? <comment><USER3> Backgroud: I have a BS in mathematics, and teach high-school mathematics. I'm working on my MS in applied mathematics part-time (in an actual classroom), but I'm considering switching over to a PhD program.

How much math have you studied? How much CS? Do you like proofs?

A degree in math is not just about knowing statistics and algorithms. You need to have the dedication to plug away at a seemingly dense problem, without visible success, for often hours at a time. If you've done a lot of programming, you might have the skill set for this already.

Beyond that, the best advice I can give to any math student is this: whether or not your teacher checks your homework is irrelevant. Do every assignment, and make sure you understand it. If you don't do so, you're probably in for a rude awakening on a test. There might be a level you can rise to, in HS or in college, without doing homework, but you will eventually hit the ceiling.

I assume an online course is twice as hard in this regard, as it's easier to put on the back burner. Start out taking only one class at a time. Get used to the level of work you'll have to put into it. It will probably be more than you're expecting.

Finally, while I can't say anything about the university you've picked out, I will warn you: a number of my math/science professors mocked the idea of getting a Bachelor of Arts in the hard Sciences, because BAs don't go as deeply into the subject matter as a BS. If you're not planning on a career change into engineering, academia or the sciences, this probably doesn't affect you, and I wouldn't worry about it. Just be aware of the bias.

<comment> excuse-me >because BAs don't go as deeply into the subject matter as a BS

Some places, like Oxford and Cambridge, only give BAs not BSs - so it's not always a good guide unless you know the institute.

<comment><USER4> Oxford and Cambridge are certainly exceptions. In general, if an institution offers both a BS and BA in the same subject (at least in the sciences), the BS tends to be more technical.

I'm not saying this to diminish the value of a BA, because what their curriculums lack in technical equivalence are often compensated for in breadth and general well-roundedness.

Of course this is not hard fact, but it's a generally correct pattern in American universities.

<comment><USER3> I hope that it was clear that I wasn't trying to diminish the value of a BA either. There is definite merit to wanting more breadth than depth, especially if you already have a job. I just wanted the OP to be aware of the biases out there. The school he's looking at doesn't offer a BS in Math, but it does offer other BSes.

<comment><USER5> > The school he's looking at doesn't offer a BS in Math, but it does offer > other BSes.

Sounds similar to UC Berkeley. The do offer BSes, but not in math.

Here are some majors that offer only BA, not BS:

       math, applied math, physics, earth and planetary sciences,
       molecular and cell biology, astrophysics

Here are some majors that offer only BS, not BA:

       chemical engineering, nutritional science,
       molecular environmental biology, molecular
       toxicology, business administration,
       engineering

And here are some that offer both:

       chemistry, computer science, environmental sciences

The reason the latter three offer both is that you can take these from two different colleges. You can get your computer science degree, for instance, from the College of Engineering, in which case it is a BS, or from the College of Letters and Science, in which case it is a BA.

There are also schools where the only difference between the BA and BS is in the requirements for electives outside your major. For instance, I recall one school where a BA required a certain number of units in a foreign language. The BA and BS required the same total number of units and the same required courses in the major--the BA simply required that you include in your electives a foreign language.

There are even schools where the requirements for BA and BS are exactly the same. When you fill out the form where you tell them how you want your name spelled on your diploma, you also check a box to say whether you want it to be a BA or BS.

When interviewing a candidate, you really should place no stock whatsoever in BA vs. BS, unless you _know_ that his school offers both and you _know_ the differences between them. There are just too many exceptions to make any kind of generalization about the two that won't give too high of a misclassification risk.

</comment></comment></comment></comment></comment><comment><USER6> I did this but with a CS degree from an Ivy-League university. I already had two years of credit under my belt when I went back to school and it took me four years of study half-time and all three semesters (Fall/Spring/Summer) during the year to finish. Best thing I ever did.

Let me give you some advice:

1\. Start slow. Take one class to start with. Get used to the pace of lecture/study and getting your assignments done. It's very hard to work full time and also study. You will need uninterrupted space and time to get your work done.

2\. If you're taking online classes, you MUST be sure that your teaching fellow/assistant and professor are willing to communicate via email or instant message. If you can attend office hours DO IT. It helps for a professor to see you as a serious student and not as a faceless email address. GO EARLY in the semester to office hours and make it a regular thing. THIS PAYS DIVIDENDS AT GRADING TIME.

3\. Make sure your school is a "real" school. Don't go to one of those for- profit schools. Make sure that your school is regionally accredited by the REAL accrediting agencies, not the fake ones that are set up by the for-profit schools.

4\. Connect with another student (or students) and work with them. Just like for startups, it helps to be "in it" with someone else.

Good luck.

P.S. One of the guys I helped get through my program was a father of five kids (and one of the way) and he took two flights each way one day a week for a year to attend class. After 3 years he finished. He also held down a full-time job while he did this. It's do-able. You just have to commit yourself to doing it.

EDIT: more advice.

<comment><AUTHOR> This is great advice, thanks! Discerning the fake accreditation from the real is somewhat difficult. I had done some searching though and this school seems to be accredited by the same place that accredits dartmouth so I think it's legit. How can I figure out if the accreditation is worth it's salt?

Thank you again!

<comment><USER6> This guide: [http://www.amazon.com/Bears-Earning-Degrees-Distance- Learnin...](http://www.amazon.com/Bears-Earning-Degrees-Distance- Learning/dp/1580082025)

goes a long way towards helping you figure out whats legit and what's not.

Generally speaking though, you want a program that's "regionally" accredited. Here's a link:

<http://en.wikipedia.org/wiki/Regional_accreditation>

Just an FYI: I've heard that some schools that were non-profit and independent have been purchased by for-profit entities mainly for their accreditation. Caveat emptor.

FWIW, most "pure" degrees from liberal-arts or engineering schools are probably OK. If your candidate school has a sports program, it's probably OK. Go visit the university. Meet the administrative officials and check out the student body. See if they have a library. There are lots of "tells" that will alert you to the possibility that your program is more about collecting money than offering a valuable educational experience.

Just do your checking beforehand. You dont want to find out halfway through that your degree isn't worth the time or money. Dont forget that all programs within a school aren't created equally. I spent six months doing due diligence on my program and the school is VERY well known.

<comment><AUTHOR> Thanks! Bought it. Also looks like it it is regionally accredited but I'm not sure about my specific program though. That's something I'll check out tomorrow.

</comment></comment></comment></comment><comment><USER7> You may want to check out this blog written by Scott Young who is pursuing an MIT computer science degree on his own, all from their online classes.

<http://www.scotthyoung.com/blog/2012/07/04/the-diy-degree/>

<comment><USER8> He had me right up until he revealed (at the very end) that the whole thing is about getting a degree from a completely unknown mail-order University. Brand matters in higher education. UConn degree > what he got. He does a very good job of selling himself and his degree so he may be able to overcome it, but it's self-delusion if he actually thinks he's better off with the degree he has. If he applied those same salesmanship skills to the UConn degree and making himself stand out with that, he'd be better off than he is now - speaking strictly in terms of academic pedigree and how he is perceived by potential employers.

<comment><USER9> I'm not sure how you attribute "unknown mail-order University" to Excelsior. I'm willing to guess that a fair number of HR managers and several million U.S. service members(and obviously their families as well) and veterans might know very well the name of this institution. Look up Regents College if you're interested to know the history.

</comment></comment></comment><comment><USER10> Simplest advice: Structure your schedule so that you can devote one semester each to the proof-based courses: Abstract/Modern Algebra and Real Analysis.

My Story:

I earned a BS in mathematics (and BA in Philosophy/History) as a working adult (late twenties – early thirties, tech support and later developer) with a 1.5 hour commute between work and school.

I didn't have any significant difficulty until Real Analysis. That's usually the "weed-out" course for math majors and for which absolutely _none_ of my programming experience prepared me[1]. I ended up switching to Philosophy/History for a while but luckily got the confidence to try Real Analysis again before completely giving up on the math degree.

I think anyone with an aptitude for programming will be fine in the math courses that are science and engineering-oriented. However, real math is about reading and doing proofs; if you have not done much of that I would try to arrange the schedule so that you end up studying stuff like Real Analysis and Abstract/Modern Algebra exclusively in a semester.

[1] In fact, my programming experience probably hurt me because I was overly focused on the "fine logic" aspect of proof writing rather than trying to understand the big picture.

<comment><USER11> I'm starting part-time study for a joint honors degree in philosophy/math at the university where I work as a full-time web dev this September, ten days before my 30th birthday. I'm glad to hear that other people have been there, done that, and got through it.

<comment><USER10> Neat.

You and I will have a _very_ similar story. The only difference is that I started working as a full-time web developer at my university after I was already taking classes here... I got the job a couple of weeks after my 30th birthday.

</comment></comment></comment><comment><USER12> Although the popular trend is against a formal higher education I would strongly advice you to pursue your decision/wish to get a degree. Yes, perhaps you could obtain the same level of knowledge and understanding throug the studies of your own, but I found that getting formal education gives a lot more - not only you learn the subject, but you also get to understand the methods of obtaining the knowledge. And this experience, at least for me, was far more important. Can you do this on your own? Perhaps, but I doubt it.

<comment><USER13> > you also get to understand the methods of obtaining the knowledge

I don't understand what you mean by this at all.

<comment> excuse-me Learning how to learn is far more important than knowing something.

That's why maths/physics PhDs are more valuable in industry than BSc's in the exact detailed topic.

<comment><USER14> Is this reflected in earnings and unemployment rates?

</comment></comment></comment></comment><comment><USER4> I don't have any feedback on online programs or working while getting a degree, but I do have some thoughts on pursuing a math degree with your goals in mind:

1\. Although there is a lot of math in computer science, a typical math curriculum will take you well outside of what might be applicable to your goals in computer science. This might not be important to you, but it's something you should keep in mind as you think about _why_ you want this degree.

2\. I looked at the curriculum you linked, and, with your goals in mind, it actually looks pretty reasonable in terms of rigor and relevance. Based on your goals, regression analysis will be a critical subject. But, and I don't want to paint this in too negative a color, most undergrad curriculums I know go further that this program does.

3\. Unless your heart's already set on this program, or there are other considerations besides what you've listed, I'd actually suggest looking at other programs first. If what you want is a math degree, than this might be a good fit. But if what you want is a degree that will be most helpful in statistics/data analysis and machine learning (which you listed as important to you) I'd suggest looking at either an Applied Math program or a CS degree. I don't know your background, but there _are_ Masters programs in CS that don't require an undergrad degree. You would still need the equivalent working knowledge of a BS in CS, though.

</comment><comment><USER15> I have the same question about computer science.

The fact is, without the degree you cannot seem to get into a job that you like, which is about programming. I have learned unfortunately that this is true within a company I work - and I am sure the prejudices will be a lot more if I apply outside.

To elaborate, I have an advanced degree in statistics, but none in comp science. What I have is though interest, and I know I am better than the lot who typically apply for such jobs. I approached this programming oriented team, and the senior leadership were thoroughly impressed - some people in that team (at senior position than mine) actually agreed that they cannot do what many things that I have already done and showcased.

Then I did an 'evaluation' project with them, again in a month I created something that was beyond what they would expect from their own. In the end when I was told that they cannot hire me now because of some leadership decisions - as the current objective is to procure 'x%' of people with com- science degree in the team and that leaves no room for my background.

Though I doubt if I will approach that particular team again (this move frankly speaks of their guts - and I am utterly doubtful of how they can defend me in the future too if I join), I think hiring PhD's may be the norm in the industry - e.g. in other farms like Google too.

I am happy in what I am doing, but I don't like doors being closed to me just because of the background - and there is a chance that I will be happier in a programming oriented job. So, even though as of now it is a far away thought, is there a way for me to get a PhD while working in my field?

<comment><AUTHOR> Interestingly I actually have the Opposite "problem." I don't need the degree. Somehow I've managed to become a good engineer making great money. That's why I could never commit before. I made it such an economic choice. Now I'm letting it be an emotional/intellectual one and it's become obvious I need to go back.

It sounds like you're on track though. Keep at making personal projects and applying for any programmIng job you think you might enjoy eventually you'll find he intersection of the right portfolio and right opportunity. Good luck!

<comment><USER6> Let me tell you my story:

I got two years of college under mt belt and had to leave school for many reasons. Went to another university a year later to try and finish and got caught up in the building Internet boom/bust. The experience I gained was VERY valuable and it was definitely the right decision to leave school to pursue my career, but I had the nagging sense that I was missing out on some jobs because I didn't have that degree.

So I found a company that would help me pay for part of my education via tuition assistance and had relatively regular hours and went to it. When I finished the degree, I changed jobs and got a 60% pay raise.

Mind you, I already had a six-figure income BEFORE the degree.

Since then, I've changed jobs twice and each job has been more rewarding and better paying that the last. I definitely feel like my program (which was from a well-known school) helps to open doors. I feel like the degree added a multiplier to my efforts that helps me to earn credibility and break through barriers.

Like it or not, the lack of that degree will subject you to prejudice you wont be fully aware of until you're freed from it. You can certainly be successful without the degree, but having it makes enough of a difference that I'd be hard pressed to recommend someone go without it unless they were clearly an exceptional individual with a clear goal for what they wanted to do in their lives.

<comment><AUTHOR> I don't really like that that's true but I've noticed that prejudice even in myself. Thanks for sharing this. It's one more reason to hold onto.

</comment></comment></comment></comment><comment><USER16> I had a pretty intense full-time job (managing an academic library's digital services) and going to school part-time to earn my BS in CS. It was incredibly difficult to manage my time.

Every semester I would work 9-5, take classes from 6-10, go home, fall asleep, rinse and repeat. I had no time to study, but when I did, I often did other things because I had no energy or motivation. I did this for four years (and I already had 2 years of college prior to this!). It was exhausting.

My only suggestion would be to take a light workload and aim to master the subject. I breezed through most of my classes because I already knew the material. For tougher subjects (e.g. statistics, compilers) I struggled. The material wasn't that hard, but because I didn't take it too seriously at the start (when it was easy) I fell behind due to weak understanding of core concepts. Never fall into that trap. Commit to studying consistently, seriously, and keeping at pace with the class.

I only did this because I wanted a degree. I think it's a piece of trash, but I wanted a little bit of security in life (I was in my early 20s and just getting started). Since you want to learn for learning's sake, commit to that. Don't try and cut corners.

</comment><comment><USER17> A degree in mathematics requires a very large amount of effort and discipline, especially given your other obligations. Is this effort best spent on a mathematics degree, or maybe you could spend this effort differently and get what you want faster?

While point a) is a good reason to get a mathematics degree, points b) and c) are not. For point b), machine learning and statistics are much more appropriate than mathematics, and for point c), it is worth knowing that machine learning requires a fairly small subset of the mathematics you'd learn in a math degree. For example, a math degree covers many areas of mathematics (such as a heavy focus on proofs, abstract algebra, complex analysis and topology) that have no bearing on statistics and on practical machine learning. Conversely, a math degree also does not focus on statistics and probability, which are essential for data analysis.

Thus were I in your shoes, I would only study the math that is necessary to understand statistics and machine learning, and would start taking a machine learning course. The only math you need is multivariate calculus, linear algebra, and probability.

</comment><comment><USER18> My background: Double major in Mathematics and Statistics. I am currently studying for a masters in Industrial Engineering BECAUSE my math/stats degree could not secure me a job after looking for 1.5 years. People don't see the value in math and you can't make them. That's why I am going to trick them by getting a degree with "engineer" in the title and maybe I can finally make it past the HR robot resume scanners.

1.The course content looks ok. There is always some sort of crap class that the department "thinks" you should take. For you it is Mat 380 Error- correction Codes. Out of the classes you get to pick, you should absolutely consider "QSO 320-Intro to Management Science". Mathematics departments (I have been through about 4 different ones) do a terrible job of application. None of your classes except QSO 320 will have day to day usefulness.

2.If you have not paid for this degree yet I would encourage you to look up programs for the following departments. Management Science, Operations Research, Operations Management, Business Intelligence, Data Science. They usually have just enough theory to carry you but focus on problem solving methods and decision making.

3.If your future goal is to go on to a masters then to some sort of research based work, then a math degree is a great jumping point. When ever I have come into a practical application course, I crush the theory and have an advantage in the ease of absorbing the knowledge. If you are not really sure about research/MS/PHd I strongly advise against this plan. You will be disappointed in how little people understand the how to leverage math skills.

In general, school is where you pay money for the privilege of doing homework and writing tests subject to the human faults of a non-perfect professor. I would advise you to look at the course syllabi for the following Coursera classes. So much good content coming from there. At least you will be more knowledgeable of the breadth in these subjects. \- <https://www.coursera.org/category/cs-ai> \- <https://www.coursera.org/category/stats> \- <https://www.coursera.org/category/cs-theory> \- <https://www.coursera.org/course/operations>

The funny thing about that list is none of them are from the mathematics category. Math is pervasive but struggles to compete without context. Take courses with context, unless you really want to pursue an academic career.

<comment><USER19> > 1\. [...] There is always some sort of crap class that the department > "thinks" you should take. For you it is Mat 380 Error-correction Codes.

Error correcting codes are fun! Taking a class on coding theory gave me some insight on compression, cryptography, and reliable data storage/transmission.

</comment></comment><comment><USER20> I have a Ph.D. in engineering, which entailed a great deal of math. I do a lot of machine learning now. I think you'll find that proofs are the great divide between "real" math, and the more applied stuff you use in ML or CS. I suppose it is kind of obvious, but the math that _isn't_ "applied" will have very little application in any other aspects of your life.

I do get a little queasy about the for-profit schools like SNHU. It is convenient, but I'm not so sure that the quality will be that good. Your peers in these classes are probably not going to be like HN. Are there any regular non-profit schools near you that might offer online classes as well?

If I were paying for online classes out of my pocket, I'd look at something like the Stanford Center for Professional Development.

[http://scpd.stanford.edu/public/category/courseCategoryCerti...](http://scpd.stanford.edu/public/category/courseCategoryCertificateProfile.do?method=load&certificateId=1209602)

They have some interesting Data Mining and ML related stuff.

<comment><AUTHOR> Interestingly SNHU is a non-profit from what I've read though I'll admit I don't know what the real difference between that for profit is... People are still making money y'know?

Where did you see them labelled as a for profit? Or are you referring to them being a private university?

<comment><USER20> My previous job morphed from being something quite interesting, to a company running a jobs website that sold education leads. Before I left, I ran the traffic to a website selling education leads. It was many of the big online players. You should be aware that many of these schools had a pretty shady business model. Their students would get student loans, fail to finish their degrees, and default on their loans. That was Ok from the schools point of view, because for a year or two the schools were charging fairly high tuition rates. They were essentially programs for transferring money from the federal government (in the form of loans) to the schools. These are the so-called "for profit" schools. It is not their "for profit"-ness that was the problem, if you will, but the way they treated their students. The government is starting to really crack down on these abusive practices (bad for both students and the government). Many of the students were of a fairly low income background, who had never been to college. There are a number of news documentaries about this, under the "for-profit" label. It seemed from me, on the outside, that most of these students would have been better served taking classes for much less at a local community college.

I am only aware of SNHU in the sense that they were buying leads in the same space as the for-profit companies. You are right that technically they seem to be a traditional non-profit college, that has started an online program. However, that online program seems to be the tail wagging the dog in this case.....

[http://www.fastcompany.com/most-innovative- companies/2012/so...](http://www.fastcompany.com/most-innovative- companies/2012/southern-new-hampshire-university)

I am not saying that they are bad - I certainly _don't know_ that. But before I signed up, I would spend a few evening Googling their specific reputation. I would worry that this school is simply trying to hide the same "for profit" motives in a non-profit cover. I know there are other players that are doing this exact thing, by taking over a small traditional school. In particular, find out what their graduation and retention rates are for their online students. What educational backgrounds do the students have? Is their program going to be of a quality that you'll be happy with?

There are a lot of very shady schools in this space. Make dead sure that you're not getting into something you'll regret. I guess, in short, _Caveat emptor_ , there are lot of bad online degree programs.

Feel free to contact me directly (email in profile) if you have any other questions.

</comment></comment></comment><comment><USER21> I have an MS in Applied Math and work in machine learning (for the past 3 years). The only real advice I can give is I am not sure how much a BS will help (it certainly wont hurt) you with getting a job in machine learning. I ended up here but I spent my entire MS studying wavelets and signal processing. I did take a few courses in machine learning, but nothing super crazy.

I think if were in your position, I would spend six months taking free courses, writing some open source projects, making some cool visualizations with d3.js, and then leveraging that to try to get a job (or transition into a job). If I was hiring someone for a position in ML at my company, I would be more interested in seeing that type of stuff than asking questions like "How does an SVM work" or "Where did you get your BS in Math from?".

With that said, if you can afford the classes, have time to put in (a lot of time to really understand math), and you have always wanted to get a degree, go for it, and dont let anyone here stop you.

<comment><AUTHOR> I think if I were only worried about a job I wouldn't go at all as I recently moved onto the Business Intelligence team at work because of how passionate and excited I am about the subject. I want more than I job, I want to deeply understand what I'm doing and excel at it. I'm going less for the short path (that I took in programming) and more for the most enriching.

Thanks for your feedback! I really appreciate it.

</comment></comment><comment><USER22> Nothing hurts more than regret. If you are serious about this, go for it. to test yourself, grab a Calculus book - I recommend Stewart's Calculus - <USER2> challenge yourself to work though it at a reasonable, but predetermined pace (say 1 chapter per week).

</comment><comment><USER23> How will you pay for it? Furthermore, how long will it take this (for now) theoretical career in ML which will require an MS to pay off the money you sunk into your degree?

Can you afford it mentally? How much time and effort can you afford to siphon away from your work to excel at your math studies? You can't go full-bore on both.

While some on HN I'm sure have been working software engineers AND pursued a bachelor's degree AND received it in only 4 years (or less, even), the truth is that it is very, very difficult. There will be a lot of misery, and a lot of time & money spent on something that, for now, is over a decade away.

<comment><AUTHOR> I have successful career as a software engineer already so I'll be paying out of pocket. Time wise I've been discussin this with a friend who is in college in his thirties and I will probably follow in his footsteps and stop my personal programming projects while I attend.

Also since my current role at work is in the same vein what I learn will directly and immediately apply to work do that help lessen the impact at work. Even so it will be tough. Very much so you're right.

</comment></comment><comment><USER24> I've found classes in graph theory, linear algebra, probability, and statistics to be the most useful for me. Probability and statistics have much more practical applications outside the classroom.

I received a minor in math, and it's been more practical than my major (information systems). It helps you frame and understand the world differently.

Classes get much tougher once you start doing math with letters instead of numbers (usually linear algebra and up), because things transition from computation to understanding the properties of numbers.

</comment><comment><USER25> Hi there. No advice, I'm in a similar situation (i.e. a software engineer who wants to get a degree).

I have a degree in CS, but by 30 (26 now) I want to be enrolled in a physics degree, followed by something in the vicinity of aerospace engineering/robotics.

This is not because I think it will be useful for work, just because they're subjects I'm interested in and I wish I had time to be on the cutting edge of these fields. I aim to support myself + my family through some sort of SaaS product(s), so working hard on that at the moment.

Either way, best of luck!

</comment><comment><USER26> I'm working on my undergrad degree while working. it really sucks. be prepared for 4-6 years of having no friends and never sleeping. you will probably burn out in 2 years but stick with it.

I also work remotely and this helps but only a little. take your current schedule and subtract 25 hours a week from it. you won't be left with much, especially if you have a family.

</comment><comment><USER27> third year of my cs degree (which is basically a math degree for the first two years) and only one thing comes to my mind seeing ~12 ppl i knew that drop out from their math degree:

If you study for a math degree you will probably be a mathematician.

let that sink in for a while because shockingly people discover that later on.

<comment><AUTHOR> Haha that's a great point I hadn't considered. Luckily I'm good with that. I don't want to be "just a programmer" I want to have real skills that my programmIng ability can augment. That's my mental model for a recipe for success. Also coincidentally I'm drawn to study actuarial sciences if not for the huge regulation and the boring environment.

Thanks!

</comment></comment><comment><USER28> First hand experience. Almost identical background, self-taught teenager started working professionally at 18 with very little formal training. 33 years old now and almost completed a part-time math degree. (2-1/2 years to go)

Advice: don't just pursue the math that you think will directly benefit your software career.

I went into my part-time math degree thinking that because I was a self taught programmer the limiting factor in my career was lack of exposure to higher maths.

I ended up discovering that the math I enjoyed the most was the more theoretical stuff in analysis, topology, category theory, abstract algebra, etc. The applied math came easier, and I probably could have self-taught most of it, but the challenging pure math subjects have been most rewarding.

<comment><USER29> Thanks for sharing. Mind if I ask where you're getting the degree from?

<comment><USER28> Mount Allison University (Canada)

</comment></comment></comment><comment><USER30> Is this going to be your first undergraduate degree or do you already hold a bachelors? Just in case you have something to built on - there are a bunch of top notch Universities offering Masters in Applied Mathematics via Distance:

Columbia University: <http://www.cvn.columbia.edu/app_math_MS.php>

Penn State: [http://www.worldcampus.psu.edu/degrees-and- certificates/appl...](http://www.worldcampus.psu.edu/degrees-and- certificates/applied-statistics-masters/overview)

University of Washington: <http://www.amathonline.uw.edu/>

<comment><AUTHOR> Yes! This is where I want to get to. I don't currently have any degree.

</comment></comment><comment><USER31> I worked in IT into my late 30's before going to school for some of the reasons you list. I got so much out of it. When you go back, you know which courses will directly help you, and you will probably learn many new things about where your strengths and weaknesses are. This is how your situation is different from many who enter college directly from high school who may not know what they want to do. Self learning on the job got me where I was, but the education got me further. Plus it really helped how I study and learn, so even the softer skills I learned prove beneficial today. Good Luck!

</comment><comment><USER32> What makes you know that that's the right degree for you?

When you say "math degree", I don't think of something that applies to machine learning all that much! :)

Math is a huge field, and undegrad math covers a big swath of it. Have you taken a stats course yet? I would consider just taking a stats course first, and then maybe asking anybody you meet with similar interests in data logging/analysis what the relevant courses are to take.

That said, looking over the summary on that page, it does seem more "applied" than most math degrees, which is probably what you want.

<comment><AUTHOR> Yeah the program has some courses that seem directly applicable to my goals. Also, I have taken an online free course in statistics and probability from Carnegie Mellon and loved it.

I'm pretty excited by the school. It seems exactly what I want in a BA and seems well accredited as well which can be hard to find in an online program.

Thanks for your input!

</comment></comment><comment><USER33> I'm a programmer who never studied or CS or even took college level math. I'd like to do something like this too, though I don't want or need a degree. I'd just like to have a deeper understanding of algorithms and how they are used in things like graphics, animation, statistics, data visualization etc. I'd like to audit some classes at the local university but am not sure where I should start. Intro to statistics? College level calculus?

<comment> excuse-me <https://www.coursera.org> or my own personal favorite <http://www.udacity.com/>

But you have to do the work, all the problem sets, and the exam - just having the youtube video open in a window isn't enough

</comment></comment><comment><USER34> > When giving people advice around data I would like to train myself around > many of the biases we are all so prone to.

A math degree is not the best way to go about this. (I just got one myself.) It will teach you to think clearly about groups, graphs, metric spaces and all that, but it won't teach you to think clearly in real life. That's something you'll need to learn elsewhere; although it might be true that a math degree will help you to learn.

<comment><USER35> I (dis)agree with you. One thing that a math degree will learn you very, very well is the spotting of gaps in logic. That is very applicable in e.g. software engineering/programming. For example, it will make you spot missing cases in long if/else if/else chains, both in code and in requirements. In the latter case, the risk is that you will get distracted by minor holes that do not really matter at the scope, and that other people may see as "not worth discussing now, as it distracts from the main course.".

Also, reading <http://www.snhu.edu/mathematics-BA-online.asp>, my main thought was "do they call THAT a math degree?" At the very least, I would put a sticker "applied" on that. That is a judgment, but not one that judges one item as better than the other. For your ambition in machine learning, it will probably be tons more useful than what I (and from his reply, I guess philh) think about when hearing the term.

For an impression of the difference: With a MS in (abstract) mathematics, you will be able to prove properties of some algorithm or formula from some preconditions, and you may be able to generalize them to some highly abstract terminology (for an example, see <http://en.wikipedia.org/wiki/Measure_(mathematics)>, which grew about mathematicians thinking deeply about what the concept 'area' means) but you need not get any experience in recognizing those preconditions. As an applied mathematician, it is more important to have a good intuition on when an approach works then to have a good understanding on whether/why it works in esoteric cases (infinite dimensions, with less than two inputs, etc)

</comment></comment><comment><USER36> Could be worth investigating some of the free online courses that MIT and other Big Universities run.. also experience a taster of studying before getting into a longer term course

I've been looking at Masters courses online recently, but for 9k and very little added monetary gain, i've decided it might be more rewarding to run a side project/business

</comment><comment><USER37> Forget about "Mathematics" and study "Statistics", man. You will never need the Maths stuff for your job.

And notice I am an Algebraic Geometer, not a funny CS. <http://pfortuny.net>

Enjoy the knowledge but do not strive for what you do not need unless you do it just for fun (which does NOT look so to me).

</comment><comment><USER38> Sorry to ask in an existing topic but im looking for a online math degree also in the UK.

Can anyone provide institutions apart from the open university which offer this?

</comment><comment><USER39> Don't you need a degree to self call "software engineer"? I'm outside US. Serious question here, just to know what North Americans consider SE.

<comment><AUTHOR> Meh. If only there were some standard around it :-/

<comment><USER39> like this? <http://www.bls.gov/soc/2010/soc150000.htm#15-1100>

<comment><AUTHOR> Am I crazy or is software engineer not listed? I guess using that at all goes against your "standard"? Hmm.

</comment></comment></comment></comment><comment><USER40> Why math and not computer science?

</comment><comment><USER41> .02 from someone who does data analysis / ML and has an undergrad in math:

A math undergrad is a nearly total waste of time. If you want to do data analysis, learn to do data analysis. Real analysis and proofs and abstract algebra and diffeq are fascinating yet utter wastes of time.

If you want to learn useful stuff, take: applied calc, applied linear algebra, applied probability, applied stats, applied ML. And nothing else. All the skills you build proving stuff are, at best, tangential. And you don't need a bit of it to do things like derive gibbs samplers or EM samplers.

If you can take an activity such as someone interacting with ads, model that as a graphical model, derive a gibbs sampler and implement it, you'll be worlds ahead of even most grad students. Focus on getting there and it should be great for your career. But a math degree is just a shiny distraction.

Oh, and one more thing: if you want to work in a particular area, then a degree _in that area_ may be useful. Eg bio, genetics, chemistry, fluids, optics, etc.

edit2: Please don't think I'm arguing against you getting a math degree. If you want one, get one. Just understand it's probably at least 80% intellectual masturbation instead of job skills. For example, as far as I can see in production machine learning, there is virtually no integration. Oh there are integrals all over the place but none of them are feasible and they'll all have to be numerically evaluated or worked around. So all those integration skills people spend endless hours learning are basically useless because the real world has virtually zero nice integrals. So understanding how to manipulate integrals and how to numerically evaluate them is very valuable, but not well covered in virtually all calc classes.

edit3: consider looking at the community colleges in your state. They often are stupid cheap and offer online courses.

<comment><USER42> Regarding your opening line: leave it to a mathematician to forgo units. I assume you meant $0.02.

:)

\- a sarcastic engineer.

</comment></comment><comment> excuse-me I can't offer any specific advice about the place but I can say - go for it.

Apart from the personal satisfaction of being a mathematician you go straight to the top of my interview list. Anyone with the dedication and commitment to do a maths degree on their own is the sort of person I want to talk to

My (admittedly personal and biased) guide is maths/physics and pref. advanced degrees first.

Followed by CS degrees from really top notch schools and then I ask why, if they are so smart they didn't do maths/physics at MIT? Acceptable answer is a complete overarching love of computer science.

Followed by no formal qualification devs - with some evidence that they have read/learned more than simply the SDK they were using.

And last on the list are CS grads from some no-name, anyone can get in, CS school. People who did a CS degree because their school counselor said it would get them a well paid job.

<comment><USER43> And here I'm a no-formal-qualification dev with many years of experience, now considering getting a CS degree from a no-name anyone-can-get-in school just because it's a prerequisite to being allowed into the US on an H1B or TN visa (because, as HN discussed yesterday[1], Canada has no tech scene.) You'd skip over me, no?

[1] <http://news.ycombinator.com/item?id=4275634>

<comment> excuse-me There are no absolute statements.

I was just highlighting that while many bad jobs insist on a CS degree, many good ones treat a CS degree with some suspicion.

See also [http://www.joelonsoftware.com/articles/ThePerilsofJavaSchool...](http://www.joelonsoftware.com/articles/ThePerilsofJavaSchools.html)

<comment><USER44> "There are no absolute statements."

This is exactly the kind of trap that will send a mathematician off on a few minute or years long tangent.

I know it contributes little; given the context i couldn't resist.

<comment> excuse-me It was intended as a Godel-joke !

</comment></comment></comment></comment></comment><comment><USER45> zaide arrieta</comment>


Silicon Valley Shaken as 19 Startups See Their Valuations Slashed - <AUTHOR> http://www.vanityfair.com/news/2016/02/silicon-valley-shaken-as-19-start-ups-see-their-valuations-slashed <comment><USER2> But how are the dragons doing in contrast? I never see any news about them anymore. I presume they're just fine, and boring success isn't newsworthy. I'd love to see how wide the gap exists between the dragons and the unicorns now vs 2013/14, and what we can learn from that rather than obsessing over the 'corns.

<comment><USER3> Dragons?

</comment></comment><comment><USER4> The markdown / write off party begins.

Here is advice from someone who mentors and invests in many startups and echoed also by PG:

All the $ in the world will not be able to buy back the chance/time concerning whats possible in your early 20's such as backpacking around the EU or hiking in India.

My two cents.

<comment><USER5> Or late 20s.

The best thing I ever did was turn down a management path cherry job to take a leave absence and, uh, backpack around the EU then hike in India.

I was supposed to be gone 3 months.

I came back after 10 to a new life.

Best thing I ever did!

* except also somehow convince my wife to wait it out for me those same 10 months. We now have two girls in SF public school.

<comment><USER6> ...or 30s or 40s or...

</comment></comment></comment><comment><USER7> > Only 12 new start-ups reached unicorn status in the last three months of > 2015.

You mean less people are doing whatever they can to get valuations at exactly $1 billion? fortune.com/unicorns/

</comment><comment><USER8> "First Round's Fred Wilson" \- how do you get this wrong?

</comment><comment><USER9> I don't think this is worthy of being a story anymore.

Remember that as public companies, GOOG, MSFT, FB, etc are all marked up and down many, many, many times a day.

Private companies can't be marked by a market so they get evaluated much less often, usually once a month to once a quarter depending on what type of firm owns them.

As someone who has gone through how to evaluate holding equity in a private company, I can say its really an exercise in two things:

1) what will your auditor allow, this usually has lots of wiggle room and they are just looking to see if you can justify your valuation.

2) What you can sell if for. This usually is the more stringent requirement.

Most of the time it really doesn't matter as you don't/can't liquidate your holding in 30 days. But it can become an issue if you have a large redemption.

See a Matt Levine writeup on this where CPP sued a famous hedge fund for writing down some non liquid debt during the period where CPP wanted to redeem and then marking it back up in the months after they redeemed.

[http://www.bloombergview.com/articles/2015-09-28/bond- prices...](http://www.bloombergview.com/articles/2015-09-28/bond-prices-and- banker-mistakes)

<comment><AUTHOR> Is it wrong to assume that investors of Fidelity's size have access to company's metrics, and whatever metrics they were tracking in their valuation model are under-performing compared to expectations?</comment></comment>


Rent vs. Buy Visualization of Top 50 Cities - <AUTHOR> http://trulia.movity.com/rentvsbuy/ <comment><USER2> Hi everyone,

Thanks for your feedback & questions. Just wanted to chime in and hopefully clarify the methodology that goes into Trulia's Rent vs. Buy Index. To make an apples-to-apples comparison, we only looked at the median list price and annualized median rent for two bedroom apartments, condos and townhouses in the 50 largest U.S. cities based on population. As such, this index does not look at single family homes.

To calculate the actual ratio, we divide the median list price by the annualized median rent. Here's a sample Price-to-Rent Ratio Calculation: \---Median List Price: $140,201.37 \---Median Rent: $1,871.65 \---Price-to- rent ratio: $140,201.37 ÷ ($1,871.65 x 12) = 6

To interpret this ratio: \----Price-to-Rent Ratio of 1-15: It is much less expensive to own than to rent a home in this city. \----Price-to-Rent Ratio of 16-20: It is more expensive to own a home in this city. The total costs of ownership of a home in this city are greater than the costs of renting, but it might still make financial sense depending on the situation. \----Price-to- Rent Ratio of 21+: The total costs of owning a home in this city are much greater than the costs of renting.

By using 15 as our baseline for the interpretation key as opposed to 12 (which would only account for a year's worth of rent), we are able to account for the additional costs such as property tax and homeowners insurance.

Of course, we understand that the decision to buy or to rent is a deeply personal decision based on ones unique financial situation. The Rent vs. Buy Index was designed to be a guide to help folks gauge whether it's more affordable to buy or to rent a home in one of the 50 largest cities.

Feel free to contact us with any additional questions. We love the lively conversation and appreciate everyone's comments.

Cheers! Daisy Kong PR Manager, Trulia firstname.lastname@example.com

<comment><USER3> This is a great infographic idea, but the census 'incorporated city' boundaries/populations is not that good of a data set for this use case.

Metropolitan statistical areas would've been a more reasonable choice here, since in many cities the city proper (as defined by incorporated bounds) is either vastly under or vastly over-priced compared to where people actually live, not to mention throwing off the relative populations.

As an aside, the way my map renders, Baltimore is north of New York =P. Great job though, and kudos to your developers for not using flash =)

<comment><USER4> The difference between metropolitan statistical areas and cities is particularly noticeable with respect to Miami.

The city itself is only the 42nd largest in the country (population 450K) but the MSA (which includes Fort Lauderdale and many suburbs) is the country's 7th-largest (population 5M+).

<comment><USER5> Similar situation for DC. The city proper has 600K, but the DC metro area (the parts of VA and MD near DC) has about 5.4M.

</comment></comment></comment></comment><comment><USER6> Very very cool!

I'm wondering why they chose 15 / 20 as the cutoff ratios though. I'm a licensed real estate agent in NYC and I've helped a number of clients make purchases where it was actually cheaper to buy than rent (usually a studio or 1BR, or outside Manhattan).

It seems like you can finance a home purchase these days at 5% or less on 30-year fixed. Add in the mortgage interest tax deduction and you are really borrowing at 3.00% (assuming your marginal tax is 40% including state / local taxes, which would be true of anyone buying a $1.3M 2br as referenced in the site).

That seems to justify a break-even ratio of about 33, not 16 or 20. Of course, you do have to add back HOA dues / coop maintenance + property taxes, and the nasty transaction costs for buying and selling. That is somewhat tempered by your rent (and property values) going up with inflation while your mortgage payments are fixed. Therefore, all the usual disclaimers apply that you need to be willing to stay there and own the property for quite some time.

EDIT: clarified that 5% rates are for 30 year fixed mortgages; 15-year amortizations would get 4.25% or so, changing by the day.

EDIT2: The tax deduction is LESS good in other metro areas. When I used to live in Redmond, WA, my marginal rate was not 40% (there is no state income tax in WA and houses are much cheaper). Also far more subtle but often ignored, in Washington most renters would take a standard deduction and only home-owners would itemize their deductions. Itemizing mortgage interest means you lose out on the standard deduction. In NYC, just about everyone itemizes because state / local income tax is already compelling enough to do so, therefore almost all the mortgage interest is deductible except for the amount subject to Pease provisions.

<comment><USER7> I agree. I just ran the numbers for SF. Based on mid-point of Trulia's buying and renting price ranges ($750K to buy, $3.25K monthly rent), I get the following annual real costs:

      buying:  ~$24K
      renting: ~$36K

That is based on the following assumptions: 40% margin tax rate, principal repayment is not a real cost (it's a saving account...) 15% down payment (renters invest the equivalent amount in a 3% annual return fund), 30 year ammortization of loan with a 4% rate (available now on 5 year ARMs -- you can always go back to renting in 5 years, and if rates soar then that means the economy has recovered, which means your house is worth more..), property tax of 1.16%, closing costs of $10K (that's high), spread over 5 years, home-owner insurance of $600 per year (that's what I pay), no insurance for renters

EDIT:

      less risky buying option : ~$30K

(now assuming a 5% loan (30-yr fixed), and PMI insurance of 0.5% of loan value, per year - require for less than 20% down)

There are many good replies to this thread, that essentially point out that buying a house is risky, and that my assumptions do not deal with any 'bad case' scenarios. But nor do my assumptions deal with any 'good case' scenarios (house prices being higher in 5 years time in _San Francisco_ \- it might just happen..) But the topic of the original article is about costs, not risk, so I kept the topic at parity, and only dealt with costs. If I were advising anyone for real on rent-vs-buy I would strongly encourage them to consider the risk and reward element of the rent-vs-buy decision, in the context the general financial situation.

Summary: buying is riskier than renting, and it can also be substantially cheaper. Right now, with a 30-yr fixed mortgage, it's cheaper. You have to take on the 'house price risk', but that also carries a potential reward, as this is San Francisco..

<comment><USER8>
       > 30 year ammortization of loan with a 4% rate (available now on 5 year ARMs)

You realize that's how a ton of people lost their homes, right?

<comment><USER7> That's only a part truth. My example specifically deals with _San Francisco_ (because Trulia showed it to be a 'rent not buy' city). In SF there have not been anything like the level of defaults seen elsewhere in the US. Elsewhere in the US, rate adjustments on ARMs were just one part of the problem. The other bigs ones behind the recent crisis were: over inflated house prices (in SF, prices were only down ~15% on peak); people qualifying for loans that they could not afford with-or-without rate changes (by lying about their income); people being unable to re-mortgage now because they have now equity/down- payment (tightening lending criteria as a result of previous over-loose criteria)

Summary: what you say is a true statement about _part_ of the reason the _US_ housing economy blew-up. But it's not very relevant to my example about buying a $750K house in SF with 15% down and a mortgage that you can actually afford (the only type you can get today - i.e. $100K in income)

<comment><USER8> My point is that you're taking on significant risk with a cavalier attitude. Let me try another:

      > if rates soar that means the economy has recovered and your house is worth more

You realize that LTCM went bankrupt betting on asset price correlations?

<comment><USER7> Well, the intention was not to be _cavalier_ , but to try to ignore the risk side of the equation as much as possible, because thats what Trulia did, so the analysis could be comparable. Having read all the subsequent comments regarding risk, I now see that what I should have said is _comparing renting to buying on a _cost only_ basis, w/o considering the differences in risk, is not a helpful analysis._

I still stand by the original assertion: buying in SF can be cheaper than renting (see the revised numbers), and the risk and reward there entailed is actually pretty small if: buying now (after a recent fall), getting a 30-yr fixed rate, and sticking around for ~5+ years

<comment><USER5> What does it mean to consider cost without considering risk, when the risk is that the cost may become more than you can afford?

</comment></comment></comment></comment></comment></comment></comment><comment><USER9> I was hoping to see how affordable it is to buy in different cities around the world. Unfortunately, this data covers 50 cities in just one country.

It should really be the "Top 50 Cities in the US". The US-centric nature of websites like this is even more irritating when they don't state it up front.

<comment><USER10> _Trulia's Q1 2011 Rent vs. Buy Index provides guidance to help you make a smart decision on whether it is better to rent or buy in each of America's 50 largest cities by population._

<comment><USER9> I meant on this site. People coming to it from a different direction might have more context or be less geographically distributed.

</comment></comment></comment><comment><USER11> The choice of a red-green gradient is probably not wise, considering the prominence of people with red-green colorblindness. ( Screenshot <http://bit.ly/fcRHRk> vs filtered screenshot <http://bit.ly/frqlxP> — Note the similarity of NYC and Jacksonville.)

Otherwise, I really dig the execution of the map.

EDIT: Cached the filtered screenshot so as to not hit the (relatively slow) colorfilter.wickline.org server.

</comment><comment><USER12> I have come to the conclusion that buying to occupy is no longer a rational decision.

Consider a grid. On one axis, housing purchases are cheap or expensive. On the other axis, the local economy is vibrant or moribund.

Hence:

      * Cheap + Vibrant: Basically doesn't exist.
      * Cheap + Moribund: Bad place to buy, you're tied to a high-risk location.
      * Expensive + Vibrant: Purchase cost will eat up the advantage of the local economy.
      * Expensive + Moribund: Get out ASAP.

Why buy anywhere?

Similar logic applies to buying to rent. Why not diversify? Long term rates of return on share indices are competitive with property and do not have mortgage risk. They also don't have local property market risks. Vanguard will set you up with an international share fund, hedged or unhedged, very cheaply and easily.

<comment><USER13> > On one axis, housing purchases are cheap or expensive. On the other axis, > the local economy is vibrant or moribund.

Neither of these things is binary.

<comment><USER12> If it wasn't clear, I'm using "axis" in the sense of continuous values.

<comment><USER14> So then look for Cheap + Improving.

<comment><USER12> Not a bad idea, but it assumes that you can forecast local markets. And you're still left with mortgage risk.

</comment></comment></comment></comment></comment><comment><USER15> The statistics on this infographic are misleading. It does not cost 200,000 to buy a house in San Diego or San Jose!

Maybe the average for downtown San Jose and San Diego are close to 200k, but that is the poorest area of both cities and not what should be used to compare. The green bubble on the point for San Diego should be much much smaller in radius(like miniscule), otherwise you think the 200k number refers to the entire city!

People should not be using this to make informed decisions (obviously).

<comment><USER3> I believe that they're basing this data on stats collected by the census, so you have take the city as defined by the census bounds, which aren't necessarily similar to common conceptions of what area is 'in' a city.

<comment><USER15> There are many cities in the county of San Diego. The city of San Diego (where you are suggesting that the 200k number came from) is about 10-20% of the size of the county of San Diego.

They should make the size of the bubble smaller to only cover the area of the city like you are saying.

<comment><USER3> The issue isn't really the city scale then, it's the numbers for the avg house price: [http://www.trulia.com/real_estate/San_Diego- California/marke...](http://www.trulia.com/real_estate/San_Diego- California/market-trends/)

[http://www.trulia.com/home_prices/California/San_Diego- heat_...](http://www.trulia.com/home_prices/California/San_Diego-heat_map/) breaks it down better, my domain knowledge of SD ends there, I couldn't tell you whether they're showing an accurate pic of what constitutes most people's idea of San Diego.

The circle is definitely scaled correctly though, the ratio of area of the circle to population (1306300 people per 1809 pixels, or about 722 people per pixel) is within the margin of error for my numbers for new york (about 662ppl/pixel), and LA (about 725ppl/pixel).

</comment></comment></comment></comment><comment><USER16> The decision to buy is prone to two major risks:

1\. That the value of the property will fall.

2\. That you will be offered a better job in another town and it's too expensive to move

<comment><USER17> A third risk (technically subsumed by 1): your local economy tanks, driving down both your income _and_ the value of your house.

Buying a home to live in is a form of un-diversification.

<comment><USER18> A fourth risk: Fed raises interest rates then your monthly mortgage payments cost more than renting and hopefully not more than you can afford.

<comment><USER19> If interest rates go up and the person who you're renting off has a mortgage on the place and his interest rates go up - your rent will go up.

<comment><USER17> Then you move out and rent from someone who isn't charging above-market rates.

"Mark to mortgage" == vacancy. If you want to successfully speculate on real estate (as any homeowner does, landlord or occupant), you need to be willing to take losses over long periods of time.

</comment></comment></comment></comment></comment><comment><USER20> This visualization assumes that a condo for sale is the same quality as an apartment for rent. At least in Seattle, that is not true--there has been a rash of (ill advised) condo construction in the area which has resulted in a lot of really nice two bedroom condos for sale, with new construction and spectacular views. Two bedroom apartments on the market are nowhere near as nice--and, of course, nowhere near as expensive. That's not to say that the condos aren't overpriced, just that the distribution of supply may not be uniform in every city.

</comment><comment><USER21> I'm from Australia but now live in NYC and I've been debating the question about whether to buy or rent. It's amusing to me to see a big red circle on this graphic for NYC. I can understand why.

NYC is a special case in many ways. For one thing, from a purely financial perspective, your best bet is to find a rent stabilized apartment that is well under market value and then invest your money elsewhere, possibly on buying a property you don't live in in NYC!

In Australia, buying property is a big thing. I'd imagine that in OECD rankings for home ownership, Australia ranks reasonably highly. Interestingly, the Guardian (in the UK) years ago did a study that showed that economic growth in Europe was inversely proportional to the rates of home ownership (meaning the countries with the highest rates of home ownership--eg Spain--had the worst performing economies and vice versa).

This makes a certain amount of sense: home ownership creates a less flexible labour market.

Anyway, in Australia, it's common to not only buy the property you live in but also investment properties. Investment properties are tax advantageous (in that the mortgage interest is a tax deduction) but you pay capital gains tax when you sell (but a good investment strategy will have you never selling; you just free up the equity to buy something else). The home you own is the reverse: mortgage interest is _not_ tax deductible but your principal place of residence is capital gains tax free when you sell.

Now the thing about real estate is that it's a hedge against inflation. For example, 10 years ago you could buy a 3 bedroom house (built in the 70s) 10 miles from the city centre in Perth for <$100k. 5 years later? $350k _minimum_. There was a structural change in the economy that hasn't since reversed and doesn't look like ever reversing. Part of this was the increase in land cost but part of it is the increase in building cost (where once you could build a house for $80k, now anything less than $150-200k is unrealistic).

So if you'd rented in that time you would've missed out on that huge jump. Thing about real estate growth is that it is never smooth. It'll go through periods of high growth and others of stagnant prices if not negative price growth. So it's a long term investment (typically 7+ years).

But the real estate market in Australia is highly speculative.

I say that because I've also lived in Switzerland, which has an almost planned economy. The tax system stamps out property speculation, arguing that it is in the common good to have affordable housing. This is an opinion that I think has merit. To give you an example, if you sell a property within 2 years of buying it, the capital gains tax is 100% (iirc), meaning the entire gain is taxed.

Anyway, back to NYC. NYC has a lot going for it from a real estate perspective. It's a center for jobs but also land is a finite resource here. Manhattan isn't getting any bigger. Most industrial areas have already been converted to residential (or, more accurately, mixed residential/commercial). Manhattan is mostly gentrified now.

Betting on a limited resource is typically a good plan but the difference between renting and buying is huge here. Like a 1BR that might cost $2000 to rent will probably cost >$500K to buy and have significant ($300-600/month) maintenance fees to boot.

I really don't understand what motivates investors for that kind of return. So something will change in the future but will prices come down (or just stagnate for years) or will rents go up? If it's the former, rent. If it's the latter, buy.

So I'm really torn on whether I should position myself to buy in the future or simply resign myself to renting. At this stage I'll probably rent just because I may move around with my employer (Google) but I must admit: the prospect of owning an apartment in Manhattan _is_ appealling.

<comment><USER22> Veering off-topic, but how do people in Australia rent apartments? It seems the answer is NOT "craigslist."

Also, from just walking around Melbourne and Hobart, it seems that Australian cities are more ownership oriented than major American cities. I've seen maybe 2 "for rent" signs. Am I just not seeing the rentals?

<comment><USER21> In America it's common for one company or landlord to manage an entire building. In Australia that's extremely rare. In NYC for example, you have co- op buildings, which is a new concept to me. Australia really has no equivalent. Pretty much all apartments in Australia are "condos" in American nomenclature (it's not a word Australians use).

Real estate agents list properties for rent, typically in their windows, on their website, in the newspaper and/or on one or both of the big property websites (RealEstate.com.au and domain.com.au). That's one thing I like: when looking for a rental you only really need to check those two sites.

It's unusual to put a "for rent" (or "for lease") sign up. "For sale" sure.

You can rent something directly from the owner but it's reasonably unusual. Even if the owner finds a tenant they'll typically use a real estate agent to manage the property (do inspections, organize maintenance, take the rent and so on).

So anyway, the lack of rental signs doesn't mean anything. In my experience you only see them in front of larger buildings on the lower end of the economic scale.

</comment></comment></comment><comment><USER23> I'm confused about the populations. For example, it mentions the population of Kansas City is 143K. Wikipedia says 482,299, and "greater" KC is closer to a million. What exactly is measured here?

<comment><USER24> The population of Kansas City _is_ 143,000--Kansas City, _Kansas_ , that is. (They're mistakenly using population data for Kansas City, _Kansas_ , instead of the much larger Kansas City, _Missouri_.)

</comment></comment><comment><USER25> This data seems extremely unreliable. For example, it claims that in KC you might be better renting, then lists a buying price range of $200-$300k. Then hop over to Denver and it says buying might be better, with a price range of $100-$200k. I've lived in both cities and looked at houses in each, and it is much, much more expensive to purchase a house in Denver than in the Kansas City metro.

</comment><comment><USER26> What would be cool on top of this is if they figured in mortgage prices, the average home upkeep costs for a certain area, insurance prices, and property taxes (whew, it'd be hard) to determine if you're flat out better of renting or buying in an area over an arbitrary period of time. This has always been something I've wondered about, whether or not buying a home or renting an apartment is actually cheaper based on a bunch of different factors. In the US, there's always this big push for home ownership, but sometimes I question the wisdom (financially) of buying a home for 'equity building' or whatever else. That's not to say that owning your own home can't be totally fun and a great place to raise a family or whatever else..obviously that's pretty hard to weigh objectively, but still. I think this would be an interesting direction for this site to go.

</comment><comment><USER27> I see it as a visualization of where "old money" has gobbled up the realestate.

</comment><comment><USER10> Cleveland is included, but not Pittsburgh? Someone's a Jets fan...

On a technical note, the information in the hover bubble is mis-aligned; the right side is a space below the left side, at least on this older version of Firefox.

<comment><USER3> They just pulled the top 50 cities from the census, Cleveland is 43, Pittsburgh is 61.

[https://secure.wikimedia.org/wikipedia/en/wiki/List_of_Unite...](https://secure.wikimedia.org/wikipedia/en/wiki/List_of_United_States_cities_by_population)

(Cities vs metro areas, oh the perils of using census data.)

<comment><USER10> Ah, I see. That makes sense, especially because the actual "city" of Pittsburgh isn't all that populated.

</comment></comment></comment><comment><USER28> Use of City boundaries instead of MSA makes this inaccurate and not terribly useful as a tool for understanding anything about these markets, let alone making decisions from.

</comment><comment><USER29> The concentration of high-population areas in California does some strange things to the map when the city circles are sized by population.

The positions don't even seem to be constant. If you sort by something else, the circle move around, but they don't necessarily move back to the same place.

I have nothing interesting to add about the content of this site; I was too befuddled by its presentation.

<comment><USER30> It looks like it does not attempt to preserve geographic location exactly.

It seems to load them in alphabetical order and fits the next one as best it can given the already plotted bubbles.

<comment><USER31> (I made this)

Sorry if this is confusing! This visualization is a Dorling Cartogram, which sacrifices geographic location accuracy in order to not have overlapping points (the East Coast would be a tight unreadable bundle otherwise, as well as the Bay Area). The basemap is intentionally left as just an outline to provide some visual context.

A great example of this in action is the Olympic Medal count visualization by the NYTimes: [http://www.nytimes.com/interactive/2008/08/04/sports/olympic...](http://www.nytimes.com/interactive/2008/08/04/sports/olympics/20080804_MEDALCOUNT_MAP.html)

<comment><USER29> Thanks for the info.

I understand and accept that the location is not accurate to the map, but what was so confusing was that the locations didn't seem to be accurate even with respect to other locations, and that the location wasn't deterministic. That doesn't happen on the nytimes example.

If I toggle back and forth between sorting by population and sorting by Rent Price, the bubbles bounce around and end up in... some random arrangement. Sometimes it's reasonable, and sometimes it's bizarre.

Here's a particularly egregious example <http://i.imgur.com/ZPAno.png>

Los Angeles is SouthEast of San Diego, Oakland is West of San Francisco and San Jose is Northwest of both of them. It's hard for me to avoid being pulled out by that.

<comment><USER31> That's definitely the map's weakness. We are using a force-based model which is nice in that it is dynamic (if lazy), but does not have the same consistency as the NYTimes example. For the NYTimes I understand they baked and tweaked the layouts in advance in order to play it as an animation as well as keep the layouts in the same position, which we should probably do on future vaguely geographic explorations like this :)

</comment></comment></comment></comment></comment><comment><USER32> A note on the chart: it's very pretty, but _why_? As soon as you load it up you see cities floating around the map in a way that cities really don't. And once they stop floating around, the cities aren't quite in the right geographical locations; to find the unlabelled dot that's Oakland I had to first click on an unlabelled dot that happens to be Sacramento.

</comment><comment><USER33> "...of Top 50 [American] Cities"

It's odd seeing lists like this that focus only on a specific country, ignoring important neighbors. Take Toronto, for example. That city is more important than 40-45 of the cities listed, but since it's a few miles North of some border, it gets completely ignored.

Why not focus on a geographic region instead?

<comment><USER34> The border likely affects the availability and format of the data needed to make the calculation.

<comment><USER33> That makes sense. It would still be nice for the title to reflect that, though, rather than the ambiguous and misleading "Top 50 Cities" that it is right now.

</comment></comment></comment><comment><USER35> I was talking to a real estate broker from phoenix on my flight last weekend. He said you can buy distressed homes for < $100k and condos/townhomes for < $50k. He's got clients buying properties, renting them in less than a month, and having instant positive cash flow.

<comment><USER36> Any tips on where to find them? When I look through the mls I see very few forclosures.

<comment><USER37> I don't have any tips but you're very unlikely to find any good deals on the internet. I would identify a target area and devote 3-5 days just hitting the ground and running the numbers on places. You should know the numbers already so when you see a place you know whether it is pass/fail on inspection.

It's a universal rule of Real Estate that good deals never reach the paper, the internet or even the front window of the agency office. In fact they rarely make it past the first page of the agent's buyers contact sheet. Find an agent in the area you want to buy in, make it clear to them you are serious and give a definitive description of what you want to buy. Make it easy for them to do their job. Every agent wants to sell a place on the way back from getting a seller to sign up. Your number must be on the list of people to call. But don't give them a loose description or they will try and sell you the first piece of crud they find. Be very clear on the description and list out factors that will disqualify a property (main road, certain neighbourhood, certain type of construction, etc).

Start making offers. Sooner or later you'll end up with a place.

</comment></comment></comment><comment><USER38> Interesting how DC and LA seem to have similar numbers and yet DC is affordable to buy (because rents are slightly higher?) while LA is more affordable to rent and a much larger bubble indicating some dramatic difference that I don't see.

<comment><USER3> The circles are scaled by population, and according to the census city boundaries they're measuring LA is 3.8MM compared to DC's 600K, which is a pretty dramatic difference, although it's just an artifact of which data they chose to use for population.

Personally I think they should've measured by metro areas, although unless they have detailed lat/lon for every property they sell working out that data might've been a mess.

</comment></comment><comment><USER39> Ha. The ratio of buy/1 year rent is about 100 in Beijing.

This despite the fact that you are not legally allowed to own property in the first place - and that the average lifespan of a building is 20 years.

</comment><comment><USER40> Did anybody notice the buying range for many cities was shown starting from 0 ( e.g. 0-100k )... I wonder what that means?

</comment><comment><USER41> I live in the city and am very curious why the foreclosure rate is shown as 0%.

<comment><USER42> People who have equity in their homes don't typically foreclose, and owners in NYC typically still do. Two reasons for that. First, property values in NYC haven't dropped as much as in other areas. Second, co-ops constitute a very large percentage of the purchasable housing in Manhattan (and in some of the outer boroughs as well). Nearly all co-ops subject you to a very invasive board approval process where you need to reveal everything there is to know about your income and assets. They want to know that you're making more than enough money to meet your expenses and that you have sufficient reserves to cover yourself through any period of hardship. Co-ops also usually require a sizable down payment (almost always at least 20%, sometimes even 100%). If you seem risky, you don't get in. So there's definitely less of an opportunity for shenanigans with exotic mortgage products and the like than in other cities.</comment></comment>