A Very Normal FAQ

Questions that normally come up

I often get the same questions popping up on my videos. In the past, I’ve just answered these directly, but it’s about time that I compile all of them into a central place that I can point people to. I’ll add more questions

What software do you use to make your videos?

• Editing, Final Cut Pro X: I don’t think there’s anything special about it; it just happens to be the software that I was taught and stuck to. I use Mac, so this is also their dedicated software.

• Design, Figma: I use Figma to design all of my thumbnails and some of the visuals that appear in my videos. I used to use Midjourney to help me generate simple icons, but now I try to make my own via the pen tool. Not as professional looking, but there’s a sense of satisfaction with making it myself. I’m also teaching myself Affinity Designer, but am still learning.

• Animation, Manim (Community Edition): For notation, formulas and graphs, I use the community edition of manim, the animation engine created by Grant Sanderson of 3Brown1Blue fame.

What kind of equipment do you use?

• Machine: I edit on a M2 Pro Mac Mini with 32GB of unified memory. I think it handles my type of videos okay, but I have come into problems exporting 15+ minute videos. Not that big of an annoyance since I can chunk things into smaller parts, but just a heads up from my own experience

• Mic: My videos are faceless, so I try make sure my audio is as high quality as possible. When I can make videos at home, I use a Elgato Wave 3 on a low profile mic arm to make it as convenient as possible to do voiceover and redo lines. I also have a pop filter on it to help guard against bad voices. If I am traveling, I bring along my DJI Lavalier Mics for portability. After I do voiceover, I add some audio filters on it to further improve the quality.

Full disclosure: the links here are my affiliate links, so I will get some compensation if you choose to buy them from. Much appreciated if you do!

Can you recommend textbooks for self-study?

I find this question difficult to answer because different people may have different goals. For this question, I’ll list out a few books that I think are useful for picking up biostatistics as a skillset. I have a preference for books that are easily found/accessible and have at least partial solutions to them.

One of the hardest aspects of self-study vs enrolling in a program is feedback; it is often hard for self-studiers to know if they actually have a handle of a concept if they do not have the chance to be wrong and be corrected.

If you need to learn the basics of a model for an applied problem, then I recommend Bernard Rosner’s Fundamentals of Biostatistics.

If you’re looking to bulk up on your foundational knowledge on statistics and probability, then I recommend George Casella and Roger Berger’s Statistical Inference.

Finally, I also recommend Richard McElreath’s Statistical Rethinking. Most statistics is taught from the frequentist perspective, but current technology has made it such that Bayesian statistics are the most approachable they’ve ever been. He gives a fresh and new perspective on Bayesian statistics, and he even offers videos on it!

Please list out a set of textbooks that would cover your MS/Ph.D studies

While I think that self-study should be dedicated to gaining useable skills for your needs, I do respect the desire for more knowledge for the sake of it. People have asked me about resources for gaining the knowledge base that you’d get for a graduate program, so this is the answer for that.

For more context, watch my video on the The Big Picture of Statistics to see a breakdown of what content is expected of biostatistics graduate students. Here, I’m listing out most of the textbooks that my courses used, as well as the topic they focused on. Most courses only use a small part of a textbook.

• Probability Fundamentals: Casella and Berger’s Statistical Inference

• Mathematical Statistics: Shao’s Mathematical Statistics, van der Vaart’s Asymptotic Statistics, Wainwright’s High Dimensional Statistics

• Basic hypothesis tests: Rosner’s Fundamentals of Biostatistics

• Linear Regression: Kutner’s Applied Linear Statistical Models

• GLMs: Agresti’s Categorical Data Analysis

• Longitudinal Data Analysis: Diggle’s Analysis of Longitudinal Data

• Survival Data: Cox’s Analysis of Survival Data

• Machine Learning: James’ Introduction to Statistical Learning

• Clinical Trials: Friedman’s Fundamentals of Clinical Trials, Piantadosi’s Clinical Trials (A Methodologic Perspective)

What are the key components of your knowledge management system?

I used Obsidian to manage all the information that I gathered in my Ph.D. I also use it to power the website behind The Statistical Garden. I like Obsidian, and I support them, but any place that you can write notes and (cruically) make links between these notes is good.

My system is simple. I have one folder to hold all my notes, which each hold digestible bits of information. I also have another folder for reference notes, notes that are specifically dedicated to representing sources of information like textbooks or papers. I use templates to help make sure that notes have a consistent structure.

To make sure that related notes are easily grouped together, I use hierarchical tags. For example:

• #project will be used to denote a note that pertains to a project in general, #personal denotes that it contains information relevant to my personal life

• #project/paper2 will denote a note that is related to my second manuscript; #personal/finance means the note deals with my financial planning

Hierarchical tags are nice since they enable more nuanced searches. Even if I search for just #project tags, the results will also include any notes that have further “subtags”. Likewise, searching #project/paper2 will only look at notes with this specific subtag.

Sometimes I’ll dedicate pages to act as hubs for projects as well, just to make it easier to navigate.