Statistics graduate school advice


October 19, 2016

It’s that time of year again, the time where I find myself meeting with students thinking about graduate school in statistics. Since I often end up sending people the same things, I figured I’d pull them together into a blog post. You probably already know about the grad cafe, the professor is in, and PhD comics. These other links might not be as common.

[One of my favorite PhD comics](<]

Q: What is grad school in statistics like?

A: Here are some resources to help you get a taste:

Q: Where should I go for grad school?

A: Wherever seems like a good fit!

I really think statistics is such an in-demand field that you can get a job with a degree from virtually any school. These show my personal research interests and biases, but a couple of my favorite programs to recommend to students are:

Fun fact I recently learned– Iowa State was the first US university with a department of statistics, and Johns Hopkins the first (in the world?) to offer biostatistics!

Q: How do I get in to grad school?

A: You need lots of things to be a strong candidate, including:

  • good (but not necessarily perfect) grades
  • a decent GRE score (particularly on the quantitative section of the regular GRE)
  • a compelling story in your personal statement (email me if you want to read mine, I don’t feel like posting it on the web)
  • solid letters of recommendation, particularly from faculty members who know you well from a variety of contexts, like class, research, etc.
  • I also always recommend reaching out to people from the program you are applying to, whether current grad students, alumni, or professors to get a better sense of a program and whether you would be a good fit. Female Science Professor has a great post about what to say (and not to say) in an email to a professor.

Q: How do I succeed in grad school?

A: I recommend the following:

Q: How can I learn more?

A: I recommend getting involved in some online communities.

  • There is a ton of activity in statistics and data science on twitter. Most of the faculty and students I mentioned above have twitter accounts (some linked above, the others easy to find), and if you are into R you can get a taste by looking at the #rstats and #tidyverse hashtags.
  • Roger Peng and Jeff Leek (mentioned above) and Rafa Irizarry have a blog called Simply Statistics with all sorts of interesting statistics discussions.
  • Hilary Parker and Roger Peng (mentioned above) have a podcast called Not so standard devations, available on SoundCloud, iTunes, and many more podcast distributors.

What did I miss? What are other questions you have?