How hard would it be to study statistics at this point?
February 13, 2016 11:30 PM Subscribe
I'm thinking of starting a graduate program that requires rigorous training in statistics. It's been a LONG TIME since I've done any math at all, and even then, I wasn't great at it. Is this too ambitious?
I won't go into detail about the program, but a part of it -- just a part -- requires that you understand, and potentially do research in, areas that require a semi-advanced level of statistics. I have not done any math in at least ten years, and even then had little comfort with it. I'm willing to work hard (and would have a few months in advance to at least get some basic comfort with the subject before diving into the courses) but I'm surprised by how many people are skeptical about this plan.
And again, this is just part of a program that has all kinds of other research methods, but it does seem like an important element and I would be expected to get to a certain level, though what that is, I can't quite tell yet.
Any thoughts? Any VERY introductory resources I should check out to prepare myself?
I won't go into detail about the program, but a part of it -- just a part -- requires that you understand, and potentially do research in, areas that require a semi-advanced level of statistics. I have not done any math in at least ten years, and even then had little comfort with it. I'm willing to work hard (and would have a few months in advance to at least get some basic comfort with the subject before diving into the courses) but I'm surprised by how many people are skeptical about this plan.
And again, this is just part of a program that has all kinds of other research methods, but it does seem like an important element and I would be expected to get to a certain level, though what that is, I can't quite tell yet.
Any thoughts? Any VERY introductory resources I should check out to prepare myself?
What kind of program is it? Your question's tough to answer more definitively without knowing that and the kinds of research you'll be doing.
You could start preparing by checking out some papers in the field and look over their methodology carefully. Note the types of analyses, statistical tests, and models they used. Learn about these methods, and try to figure out why the authors used the methods or performed the tests they did. Maybe download R (free!) or some other statistical software and walk yourself through some data analysis examples taken from the interwebs if you're feeling up to it.
posted by un petit cadeau at 11:51 PM on February 13, 2016 [2 favorites]
You could start preparing by checking out some papers in the field and look over their methodology carefully. Note the types of analyses, statistical tests, and models they used. Learn about these methods, and try to figure out why the authors used the methods or performed the tests they did. Maybe download R (free!) or some other statistical software and walk yourself through some data analysis examples taken from the interwebs if you're feeling up to it.
posted by un petit cadeau at 11:51 PM on February 13, 2016 [2 favorites]
If you are conditionally accepted you will receive a plan for courses to complete as prerequisites. The programme advisor can tell you if that will be necessary.
My husband went from English BA to Economics MA, with prereqs and it was hard work but possible. A stats MSc degree might have been different
posted by chapps at 12:14 AM on February 14, 2016 [1 favorite]
My husband went from English BA to Economics MA, with prereqs and it was hard work but possible. A stats MSc degree might have been different
posted by chapps at 12:14 AM on February 14, 2016 [1 favorite]
It's hard to answer this question, because people mean different things by "semi-advanced" and they also mean different things by "not great at math." A lot of people who say they aren't great at math are perfectly competent.
I think that you need to find someone in the field to talk to. Looking at papers in the field is a good suggestion, but if you don't have the training yet you might find it hard to judge. Do you know any students in a similar program? Do you know any internet forums where you could find someone?
Can you look at the required courses? Can you find out about what non-required courses students often take?
There are some people out there who just have a mental block when it comes to mathematics. But I think you might be more anxious than necessary about your ability. I would be more concerned about your happiness, if you are anxious and uncomfortable with a large part of your program.
posted by Kutsuwamushi at 12:20 AM on February 14, 2016 [8 favorites]
I think that you need to find someone in the field to talk to. Looking at papers in the field is a good suggestion, but if you don't have the training yet you might find it hard to judge. Do you know any students in a similar program? Do you know any internet forums where you could find someone?
Can you look at the required courses? Can you find out about what non-required courses students often take?
There are some people out there who just have a mental block when it comes to mathematics. But I think you might be more anxious than necessary about your ability. I would be more concerned about your happiness, if you are anxious and uncomfortable with a large part of your program.
posted by Kutsuwamushi at 12:20 AM on February 14, 2016 [8 favorites]
I entered a quantitative social science PhD program with no post-high school math (and I never did calculus in high school) - 10 years later - and I worked hard and learned my statistics and now I am a professor. The learning wasn't that hard. I did take far more statistics courses than most of my peers though. But that was because I liked them.
If they conditionally accepted you don't stress.
posted by k8t at 1:21 AM on February 14, 2016 [3 favorites]
If they conditionally accepted you don't stress.
posted by k8t at 1:21 AM on February 14, 2016 [3 favorites]
Oh if you are a woman, let me tell you. If you don't straight up flunk math courses, I think you'll be fine. I've been in a lot of advanced math/tech/CS classes and the amount of good faith that people will extend to your average dude with swagger but not a determined woman with talent is pretty incredible. People are most likely skeptical because their brains go "girl scientist??? durrrr" and they don't get much farther than that. (Imagine if a male acquaintance told you he was going to nursing school, and then add the special flavor of sexism to that; people don't know what to think.) The suggestion to study some linear algebra (and not just know how to do it, but what it means) is a very good one.
If you were already accepted conditionally, don't worry about it, work hard, ask for help, and do your best. If you study math you might want to get more familiar with reading and writing proofs; for me being able to study math at that level made my understanding much deeper and made applied math seem like much more fun, because problem solving became more conceptual to me.
Math isn't quite like riding a bicycle but I think you'll find that coming back to it, it's a lot easier than learning it the first time around. Things that you kind of understood before but not really will now make perfect sense.
posted by stoneandstar at 1:28 AM on February 14, 2016 [2 favorites]
If you were already accepted conditionally, don't worry about it, work hard, ask for help, and do your best. If you study math you might want to get more familiar with reading and writing proofs; for me being able to study math at that level made my understanding much deeper and made applied math seem like much more fun, because problem solving became more conceptual to me.
Math isn't quite like riding a bicycle but I think you'll find that coming back to it, it's a lot easier than learning it the first time around. Things that you kind of understood before but not really will now make perfect sense.
posted by stoneandstar at 1:28 AM on February 14, 2016 [2 favorites]
My MS and PhD are in Ecology. Ecology is a very stats heavy field, but many of the statistical methods used are extremely specific to the type of data sets you're working with. So you don't need to know everything about all types of statistics, but you need to understand the assumptions and requirements and methods for certain specific tests to analyze the type of data that you have. Once you've been through a few of these, it starts to feel much less complicated, and you start to gain confidence that you can learn new techniques as needed and use them effectively.
posted by hydropsyche at 4:16 AM on February 14, 2016 [6 favorites]
posted by hydropsyche at 4:16 AM on February 14, 2016 [6 favorites]
In addition to what's been said above, if it's at all possible, carefully choose the instructor(s) you would have for any statistics class. My degrees required some statistic courses. The first instructor I had couldn't teach a snowball to melt in an oven, the second instructor could have taught a rock to float.... In a course like statistics the instructors need to understand that the math is NOT your life focus and be able to teach to non-math student.
posted by HuronBob at 4:52 AM on February 14, 2016 [1 favorite]
posted by HuronBob at 4:52 AM on February 14, 2016 [1 favorite]
in my experience, most non-maths fields don't really study statistics - they just learn and apply whatever statistical processes are commonly used in that area. and typically if you talk to someone active in that field they'll know of one or two books that are considered essential, and which describe the particular subset of "applied statistics" that you need.
so even though you say "rigorous training in statistics" i suspect all you actually need is to understand the tools used in your particular area. which really shouldn't be that hard at all - you'll need to know a little background and a bunch of recipes.
i wouldn't worry. and also, second other comments about this being something (imho) where women are both doubted more than men and seem (again, ime) to also self-doubt more.
PS so what you need to do is find out which books those are. talk to someone in the field and see what the standard books are. because learning about statistics in general is not what you need (and these books will likely be introductory enough, because they're typically used by postgrads who are starting their phd studies and so need to come up to speed).
posted by andrewcooke at 5:33 AM on February 14, 2016 [8 favorites]
so even though you say "rigorous training in statistics" i suspect all you actually need is to understand the tools used in your particular area. which really shouldn't be that hard at all - you'll need to know a little background and a bunch of recipes.
i wouldn't worry. and also, second other comments about this being something (imho) where women are both doubted more than men and seem (again, ime) to also self-doubt more.
PS so what you need to do is find out which books those are. talk to someone in the field and see what the standard books are. because learning about statistics in general is not what you need (and these books will likely be introductory enough, because they're typically used by postgrads who are starting their phd studies and so need to come up to speed).
posted by andrewcooke at 5:33 AM on February 14, 2016 [8 favorites]
I did a grad degree a few years ago and found myself in a similar situation. Humanities person, had no math since high school which was a long time ago. I wasn't required to take stats, but I wanted to because big data has become such a thing in education. It kicked my butt, but I am so glad I took it! Our school took an applied approach so we were learning everything using real (cleaned up and trimmed) data, which was both helpful and interesting.
I found my first stats class so interesting and practical, I took the next one as well. It didn't (and doesn't) come easily to me and I spent as much time working on my stats coursework as nearly the rest of my other courses combined and I regret nothing. If you're really concerned (I was too), maybe brush up on some basics via Khan Academy?
posted by smirkette at 5:37 AM on February 14, 2016
I found my first stats class so interesting and practical, I took the next one as well. It didn't (and doesn't) come easily to me and I spent as much time working on my stats coursework as nearly the rest of my other courses combined and I regret nothing. If you're really concerned (I was too), maybe brush up on some basics via Khan Academy?
posted by smirkette at 5:37 AM on February 14, 2016
Get on Khan Academy and work your way through a bunch on your own and see how fast you pick it up.
posted by Jacqueline at 5:52 AM on February 14, 2016 [1 favorite]
posted by Jacqueline at 5:52 AM on February 14, 2016 [1 favorite]
I came to say what andrewcooke said. Unless this is a grad program in math and statistics, you won't be doing "semi-advanced" statistics, and most likely if you apply yourself to rigorously learning the applied stats you need, you'll end up shocked at how incompetent your peers and sometimes instructors are.
The vast majority of scholars who use applied statistics have never learned them properly and picked up abjectly horrifying habits and misbeliefs as a result. I would much rather have a student who had spent the past few months really digging into an intro and maybe 201 level stats course online than someone who comes in and says "I already know stats really well." The latter person is usually the one who can't explain what a null hypothesis is or what p-values really mean.
As far as basic math skills go, there aren't a lot required to learn applied statistics. You might get a better grasp of some concepts if you're able to work out the algebra yourself the first time, but it certainly isn't required and most people never do the math themselves in their whole career.
posted by telegraph at 6:01 AM on February 14, 2016 [6 favorites]
The vast majority of scholars who use applied statistics have never learned them properly and picked up abjectly horrifying habits and misbeliefs as a result. I would much rather have a student who had spent the past few months really digging into an intro and maybe 201 level stats course online than someone who comes in and says "I already know stats really well." The latter person is usually the one who can't explain what a null hypothesis is or what p-values really mean.
As far as basic math skills go, there aren't a lot required to learn applied statistics. You might get a better grasp of some concepts if you're able to work out the algebra yourself the first time, but it certainly isn't required and most people never do the math themselves in their whole career.
posted by telegraph at 6:01 AM on February 14, 2016 [6 favorites]
I didn't bother with high school math after grade 11, and I aced two uni-level stats courses an embarrassing number of years later.
2nd HuronBob, though, I did have a great prof friendly to math-phobics for the first course, which helped. But if you don't wind up with someone like that, I think you can get past it by doing enough drills. (My second stats prof was less fantastic. Or is maybe fantastic in some other ways than teaching people who are afraid of math.)
And 2nd ALoD, I prepped by doing a bit of work from a pre-calculus textbook every day for a month before the first class.
(I discovered, or remembered, that solving math/stats problems is satisfying, in a way few other things are. You get an isolated problem; you do the process, you get the result. If you miss something, you figure out what it is, and apply it to the next problem. Doing exercises daily through the course helped, as well. Also (unlike humanities stuff), when you're done for the day, you put the problems away, and your heart is free. It was lovely!)
posted by cotton dress sock at 6:25 AM on February 14, 2016 [1 favorite]
2nd HuronBob, though, I did have a great prof friendly to math-phobics for the first course, which helped. But if you don't wind up with someone like that, I think you can get past it by doing enough drills. (My second stats prof was less fantastic. Or is maybe fantastic in some other ways than teaching people who are afraid of math.)
And 2nd ALoD, I prepped by doing a bit of work from a pre-calculus textbook every day for a month before the first class.
(I discovered, or remembered, that solving math/stats problems is satisfying, in a way few other things are. You get an isolated problem; you do the process, you get the result. If you miss something, you figure out what it is, and apply it to the next problem. Doing exercises daily through the course helped, as well. Also (unlike humanities stuff), when you're done for the day, you put the problems away, and your heart is free. It was lovely!)
posted by cotton dress sock at 6:25 AM on February 14, 2016 [1 favorite]
There are three levels of competence here.
The most basic is purely computational: collect the data, do the test. This would also include being able to interpret the results.
The second level is ability to choose a proper test, and to design an experiment, or a data collection plan, that supports the test. This requires a deeper comprehension of how the statistics work in your particular situation.
The third level is all about finding ways to do testing in situations where existing methods are inadequate. I strongly doubt this is required for you.
You are going to have to do the basics, and to work out applications of existing methods, but only as applies to your specific area of study. You won't have to know every test and be able to prove the theorems behind them in an oral exam. You can read the books and work it out as the need arises. It seems to me like this is about a two semester problem. Stat 101 for how statistics works, and another course on more specifically related topics. Stat 101 will require basic calculus.
posted by SemiSalt at 7:06 AM on February 14, 2016 [1 favorite]
The most basic is purely computational: collect the data, do the test. This would also include being able to interpret the results.
The second level is ability to choose a proper test, and to design an experiment, or a data collection plan, that supports the test. This requires a deeper comprehension of how the statistics work in your particular situation.
The third level is all about finding ways to do testing in situations where existing methods are inadequate. I strongly doubt this is required for you.
You are going to have to do the basics, and to work out applications of existing methods, but only as applies to your specific area of study. You won't have to know every test and be able to prove the theorems behind them in an oral exam. You can read the books and work it out as the need arises. It seems to me like this is about a two semester problem. Stat 101 for how statistics works, and another course on more specifically related topics. Stat 101 will require basic calculus.
posted by SemiSalt at 7:06 AM on February 14, 2016 [1 favorite]
Also - some universities now have dedicated stand-alone statistics services. My university offers workshops and consulting services for everyone from undergrads to faculty. (In the absolute worst case scenario, you can hire someone to tutor you.)
posted by cotton dress sock at 7:20 AM on February 14, 2016 [1 favorite]
posted by cotton dress sock at 7:20 AM on February 14, 2016 [1 favorite]
Unless you are studying statistics itself – either applied statistics or mathematical statistics – it sounds like you will need:
1) working knowledge of mathematics (for computational rules and to understand how to develop samples and understand results),
2) knowledge of statistical tools and methodologies (which can be intensive, but is not necessarily the same as maths.)
3) proficiency at using #1 within the context of #2.
Some of the more difficult aspects of statistics aren't maths / computational at all – for there are tools for that, from Excel to MatLab and beyond.
The more difficult aspects are:
1) Translating a human problem into a statistical enquiry
2) Creating / maintaining a cohesive environment from start to finish
3) Generating results that both reflect reality, and are defensible / reproducible
I would imagine a semi-advanced knowledge of statistics includes as heavy a focus on those aspects, as on the actual mechanics of collecting and manipulating data. For you can get to the first set (mechanics) without knowing the second set (application), but it's very hard to get to the second set (application) without knowing the first set (mechanics)
A perfect introduction to statistics looks like learning Mandarin Chinese. If you want to be ultimately proficient, you will learn to read, write, and speak it.
On the other hand, an adequate introduction to statistics will be to learn enough of the 1) theory, to 2) learn the tools, toward the goal of having a strong knowledge of 3) the application.
Much as it may be enough to learn to speak and read business Mandarin, without having to go into the full lessons on the written character set and extended vocabulary.
Being classically trained in statistics three times now in different manners, I will say I use the theory minimally, but certainly to enjoy the elegance of statistical maths. Very glad I spent the time to learn it, but don't often use it.
More often, I use the tools / supervise people using the the tools / create concepts that use the tools. The knowledge of the tools is invaluable, for there's a huge difference between sitting with the problem (which I want to know how many $n people in area $X sell for $Y price as opposed to people in area $Z selling for $AA price), and being able to actually describe the methodology that I want to use. "Can you tell me the mean price leather goods makers sold saddles for in Brighton, as opposed to Cambridge. Can you also give me the $MAX, the $MEDIAN, and the likely price adjusted for seasonality".
Finally, the most important thing about statistics of all is to understand the integrity and reliability of what's being asked for, and how much you can trust the analysis or resulting model. I can do all the measurements in the world and have a beautiful analytical process, but if the population / sample distribution is fucked up, then it's meaningless.
For me, semi-advanced statistics is equally about structuring the problem and interpreting results as it is remembering:
probability(k)= n over k times p raised to the power of k time 1 minus p raised to the power of n minus k.
posted by nickrussell at 7:33 AM on February 14, 2016
1) working knowledge of mathematics (for computational rules and to understand how to develop samples and understand results),
2) knowledge of statistical tools and methodologies (which can be intensive, but is not necessarily the same as maths.)
3) proficiency at using #1 within the context of #2.
Some of the more difficult aspects of statistics aren't maths / computational at all – for there are tools for that, from Excel to MatLab and beyond.
The more difficult aspects are:
1) Translating a human problem into a statistical enquiry
2) Creating / maintaining a cohesive environment from start to finish
3) Generating results that both reflect reality, and are defensible / reproducible
I would imagine a semi-advanced knowledge of statistics includes as heavy a focus on those aspects, as on the actual mechanics of collecting and manipulating data. For you can get to the first set (mechanics) without knowing the second set (application), but it's very hard to get to the second set (application) without knowing the first set (mechanics)
A perfect introduction to statistics looks like learning Mandarin Chinese. If you want to be ultimately proficient, you will learn to read, write, and speak it.
On the other hand, an adequate introduction to statistics will be to learn enough of the 1) theory, to 2) learn the tools, toward the goal of having a strong knowledge of 3) the application.
Much as it may be enough to learn to speak and read business Mandarin, without having to go into the full lessons on the written character set and extended vocabulary.
Being classically trained in statistics three times now in different manners, I will say I use the theory minimally, but certainly to enjoy the elegance of statistical maths. Very glad I spent the time to learn it, but don't often use it.
More often, I use the tools / supervise people using the the tools / create concepts that use the tools. The knowledge of the tools is invaluable, for there's a huge difference between sitting with the problem (which I want to know how many $n people in area $X sell for $Y price as opposed to people in area $Z selling for $AA price), and being able to actually describe the methodology that I want to use. "Can you tell me the mean price leather goods makers sold saddles for in Brighton, as opposed to Cambridge. Can you also give me the $MAX, the $MEDIAN, and the likely price adjusted for seasonality".
Finally, the most important thing about statistics of all is to understand the integrity and reliability of what's being asked for, and how much you can trust the analysis or resulting model. I can do all the measurements in the world and have a beautiful analytical process, but if the population / sample distribution is fucked up, then it's meaningless.
For me, semi-advanced statistics is equally about structuring the problem and interpreting results as it is remembering:
probability(k)= n over k times p raised to the power of k time 1 minus p raised to the power of n minus k.
posted by nickrussell at 7:33 AM on February 14, 2016
Hey, this was me before I did a MPP. Hadn't taken math since high school, actually changed my major in college so I wouldn't have to do stats, because I thought I wasn't good at math.
Everything was fine. I took three stats courses and three Econ courses and didn't have more trouble than anyone else. I wound up building statistical models for my thesis!
The only thing is that I would have been able to take the faster/more sophisticated versions of the courses if I had taken some calculus in school, which I hadn't. So maybe talk to someone from your program ahead of time to see what foundations they recommend.
posted by lunasol at 8:05 AM on February 14, 2016
Everything was fine. I took three stats courses and three Econ courses and didn't have more trouble than anyone else. I wound up building statistical models for my thesis!
The only thing is that I would have been able to take the faster/more sophisticated versions of the courses if I had taken some calculus in school, which I hadn't. So maybe talk to someone from your program ahead of time to see what foundations they recommend.
posted by lunasol at 8:05 AM on February 14, 2016
Just in response to your last question, look online for a free statistics course. Many universities like Harvard, MIT, Stanford, etc offer free, high-quality online courses that incude lectures and printed materials, as well as sites like edX that offer courses from different universities. A basic stats course will not be hard to find as statistics is a common college-level course.
For what it's worth, I think people are skeptical because so many people don't like math and it sounds daunting to them. You said you're willing to work hard and you're even taking the initiative to prep yourself in advance. Don't let their insecurities become your own.
posted by atinna at 9:24 AM on February 14, 2016
For what it's worth, I think people are skeptical because so many people don't like math and it sounds daunting to them. You said you're willing to work hard and you're even taking the initiative to prep yourself in advance. Don't let their insecurities become your own.
posted by atinna at 9:24 AM on February 14, 2016
I quit taking math after Trigonometry in high school (i.e., no pre-cal, no calculus). Had to take an algebra test once I got to college to satisfy the math requirement. 14 years after my last math class, I started grad school. I became a TA in Statistics in my 2nd year. It's really not about math, it's about knowing which tests to apply to which situation. The software does the math for you. Did you take algebra at any point in your life? Brush up on that. You'll be fine.
posted by desjardins at 9:51 AM on February 14, 2016
posted by desjardins at 9:51 AM on February 14, 2016
Nthing the many others who said that if this is something like a social-science-that-isn't-econ or education, everywhere except maybe the veeeeeerrrry top programs will expect you to walk in knowing little or nothing about statistics and math and will pick up from there, and that they will probably expect to get you to a level where you understand how to ask the computer for results, can interpret the results, and know which tool to use when.
But just to note that, contra HuronBob, in a graduate program you will probably have no choice at all about who your instructors are. It's more common that this specific course is required in your first semester, so you take that course from whoever is the instructor that semester.
If your program is not econ, not (something-)statistics, and not math, I wouldn't go looking at the methods in current articles. That will just be incomprehensible gobbledygook right now, just like a text in Russian would be if you don't understand Russian. Similarly, I wouldn't bother trying to teach yourself intro stuff now through Khan Academy or free MOOCs or whatever.
Instead, you can be confident that if you are accepted into the program, they think you can do it, and once there they will be invested in you successfully learning the stuff. You do not need to guess about how much you need to know going in. If they want you to take a linear algebra class ahead of time, guess what, they will tell you this. If they want you to do a math boot camp before the semester starts, they will run one or send you to one.
But also just to say, just because being admitted would mean they think you can almost certainly do the stats doesn't mean that entering the program is necessarily smart for you to do, and that there are many reasons to be skeptical about the idea of entering a graduate program that have nothing to do with your ability to learn statistics.
posted by ROU_Xenophobe at 10:35 AM on February 14, 2016 [1 favorite]
But just to note that, contra HuronBob, in a graduate program you will probably have no choice at all about who your instructors are. It's more common that this specific course is required in your first semester, so you take that course from whoever is the instructor that semester.
If your program is not econ, not (something-)statistics, and not math, I wouldn't go looking at the methods in current articles. That will just be incomprehensible gobbledygook right now, just like a text in Russian would be if you don't understand Russian. Similarly, I wouldn't bother trying to teach yourself intro stuff now through Khan Academy or free MOOCs or whatever.
Instead, you can be confident that if you are accepted into the program, they think you can do it, and once there they will be invested in you successfully learning the stuff. You do not need to guess about how much you need to know going in. If they want you to take a linear algebra class ahead of time, guess what, they will tell you this. If they want you to do a math boot camp before the semester starts, they will run one or send you to one.
But also just to say, just because being admitted would mean they think you can almost certainly do the stats doesn't mean that entering the program is necessarily smart for you to do, and that there are many reasons to be skeptical about the idea of entering a graduate program that have nothing to do with your ability to learn statistics.
posted by ROU_Xenophobe at 10:35 AM on February 14, 2016 [1 favorite]
Wow, I'm overwhelmed everyone! I probably should've given more info, but it's hard to know what I don't know. It's a social science course (not econ). I'm feeling encouraged, and am meeting with someone else in the department soon who can hopefully tell me more about what's at stake. Still, this gives me some assurance that I think I can actually do it. (It's not clear how much I would have to use it, versus understand it.) Many thanks!
posted by EtTuHealy at 12:16 PM on February 14, 2016
posted by EtTuHealy at 12:16 PM on February 14, 2016
you seem to have posted with a sockpuppet? who posted another q on the same day. oh dearie me... (edit: just thought of partners and came back to reduce cynicism!)
posted by andrewcooke at 12:18 PM on February 14, 2016
posted by andrewcooke at 12:18 PM on February 14, 2016
Not a sockpuppet, my partner's account! Apologies!
posted by EtTuHealy at 12:20 PM on February 14, 2016 [2 favorites]
posted by EtTuHealy at 12:20 PM on February 14, 2016 [2 favorites]
This thread is closed to new comments.
posted by a lungful of dragon at 11:38 PM on February 13, 2016 [2 favorites]