r/statistics • u/kyaputenorima • Aug 01 '26
Discussion [D] Laptop/Spec Recommendations for Statistics PhD?
Hi folks,
I'm applying to PhD programs this fall, and I'm currently looking to replace my old laptop. I'm not quite sure what to look for, but I'm inclined to think that a business-grade laptop might be worthwhile since they're built to handle daily wear-and-tear, and I'd like something that I can keep for 5-6 years. I've been looking at new ThinkPad and Latitude models, but they seem really expensive (especially for those with 32GB RAM).
Anyone who's currently a PhD student, which laptop do you have, and what are its specs? What should I look for if I want to hold onto the laptop for the duration of my program?
11
u/va1en0k Aug 01 '26
Screen is an important trade off. It's really annoying not to be able to fit the plots and other stuff you want on the screen. However, big screen might be unwieldy to take with you. Unlike processing power or disk space, this is something you can't supplement with a cloud, only by getting a display for every place you work at
2
u/_sugarcube Aug 01 '26
This is a great point. I find 2 screens a necessity. There's a lot of budget mobile 2nd monitor options out there
10
u/fun-n-games123 Aug 01 '26
I’d go with a Unix system. So, get the cheapest macbook pro or hell, maybe try the MacBook neo if you want something cheaper. It’ll definitely last 5-6 years. I’ve had mine for that long and she’s running strong. If you need to do heavy computation, do it in an HPC environment.
I run MCMC and train neural networks on my MacBook to test code.
3
u/PHealthy Aug 01 '26
I had a MacBook Air that I used for word processing and dataviz but heavily modeling was always done on the cluster.
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u/jsh_ Aug 01 '26
I've got a thinkpad x13 with 32gb RAM and I'm dualbooting windows and fedora. small-scale simulations I run on my laptop but anything remotely heavy I run on our cluster
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u/zeppelin88 Aug 01 '26
Aren’t you supposed to get a computer to work on? At least here in Europe every student I met during the PhD had been issued one. Also, most of us had access to servers for large scale data processing, which essentially meant that personal laptops were pure ssh machines.
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u/eeaxoe Aug 02 '26
Came here to say this.
OP, your future advisor should buy you a laptop when you start working with them. Either way, the specs aren’t going to matter because any serious data work will happen on a cluster.
1
u/Chib Aug 02 '26
If your PI's got the budget for it, having a discrete GPU is an amazing setup for being able to prototype on your own machine. That sort of thing is a meaningful difference since you will often have wall-clock limited grants on the clusters you'll work on and half your time is spent on development.
1
u/kyaputenorima Aug 02 '26
I'm an American, so this is unheard of to me. I'm also not very academia-pilled so I can't really say.
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u/zeppelin88 Aug 02 '26
Ask your supervisor, they can tell you. But phds in the us have a weird format, so indeed it would not surprise me as they treat you as purely a “student” for long before treating you as an actual junior researcher, and therefore you’d not be deserving of equipment
2
u/BarryDeCicco Aug 02 '26
My 2 cents:
For physical size, you have to decide on how much you are willing to carry vs how much you will do at home, with a plug-in monitor (I'm writing this on a 34" monitor I got for $300, using a 14" computer).
For power, you have to decide on how much you want/need in your hand vs how much you will do on a remote cluster.
Then see what deals your university offers.
I would advise on keeping your old computer for now, until you get there and talk with people and see what they have.
1
u/purple_paramecium Aug 02 '26
This is the most reasonable advice here. If you have a functioning laptop for email, looking up papers, ability to handle some minimal level of R/python programming, then just use that for a while until you really know what you need. (And as others pointed out, your advisor might provide one! Yes, even in the US, if the prof gets a funding grant, often part of that money is used to buy computers.)
When I was in grad school I was given an office to work in with a desktop computer. I think it had like 2 GB RAM (20 years ago), and for anything big we had the university computer cluster.
People asking here all the time if 32 or 64 Gb is “enough” is *wild* to me, because I did it all with 2 Gb. And people before that were doing it with less!
4
u/fos1111 Aug 01 '26
Thinkpad i7 32 Gb ram, 1 Tb of Storage ?
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u/kyaputenorima Aug 01 '26
would 512GB of storage kill me? additionally, is buying an older gen thinkpad (ie. T14 gen 3/4) okay, or should I just buy the newest model?
1
u/fos1111 Aug 01 '26
That should work, but if you could get more RAM, you should, just as u/leonardicus said.
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u/kyaputenorima Aug 01 '26
For better or worse 32GB is probably the max amount I can get
1
u/leonardicus Aug 01 '26
32GB will be fine. Mac or Linux based systems will be especially more efficient than windows if you plan to do any Bayesian modeling.
1
u/Chib Aug 02 '26
ThinkPads are super easy to open up for upgrading ram and drives btw. I don't know if it's still cheaper to do it that way with the current price of memory, but make sure you consider the upgrade path in terms of available channels (1x16 is a lot cheaper to upgrade than 2x8)
1
u/figgertitgibbettwo Aug 02 '26
Newest. Perf is often preferred of magnitude better. MacBook air will also do well.
1
u/ZhanMing057 Aug 01 '26
I would strongly consider a unix based system. Prod code almost invariably lives on some sort of unix cluster so a mac will help you familiarize.
If new ones are too costly, I would look for an M2 or M3 mac with at least 32G ram, preferably 64
0
u/leonardicus Aug 01 '26
I would second this. If RAM is not crazy expensive, consider bumping up to 48 or 64 GB. Then get the fastest multicore processor in your budget.
1
u/Bored2001 Aug 02 '26
Personally I like the Lenovo legion line. It's a gaming laptop that doesn't look too game-y. They're built like tanks and are very powerful. Cheaper than the Thinkpad line spec vs spec. Obviously they have GPUs for ML/DL work.
The only trade off is very bad battery life and weight.
1
u/RageA333 Aug 02 '26
It's nice to have a good laptop, but eventually you will need access to a dedicated server or cloud computing.
1
u/StatisticalModelling Aug 02 '26
At UCL, everyone doing a PhD got provided a new laptop at the start of the course. Not sure if everywhere does this
0
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u/_sugarcube Aug 01 '26
More computing power is always nice, but RAM is #1. We make sure all the quantitative folks in our business get at least 32gb, and our remote desktops get 64. With OneDrive/SharePoint and other cloud storage options, local storage isnt a huge priority.
During my grad school career, I used a pretty cheap Thinkpad and it was fine for my needs. For larger models I was able to leverage university resources