No Bullshit Guide to Statistics progress update

Over the years several readers have suggested (sometimes demanded!) that I write a book on statistics. Indeed, since the company’s mission is to make the most useful parts of math accessible to the people, it makes sense to pursue statistics as the next title. Statistics is some of the most useful math out there! The 21st century is going to be all about data, so it makes sense to learn about the concepts and tools you need to analyze data, discover patterns, and make decisions.

I’ve now been working on the No Bullshit Guide to Statistics for three years so I figured it’s about time for an update to let y’all know how it’s going. My goals with this blog post are to share with you the detailed book outline and chapter previews, and also ask for your help to validate certain assumptions about the readers’ background (math and programming skills) and their motivation to learn statistics. Please jump to the short survey before continuing with the rest of the blog post. It won’t take longer than 2 mins.

 

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Fixing the introductory statistics curriculum

Let’s talk about the problems with the teaching of statistics. Understanding statistics is essential for many fields of academic research, and also useful in industry. Why is it that first-year statistics courses sucks so bad? It seems that conceptual understanding of statistics ideas only marginally improve after taking a STATS 101 course. Is this because statistics is a really difficult subject to teach, or are we teaching it wrong?

I’ve been looking into this question for the last three years and I finally have a plan for how we can improve things. I’ll start wiht a summary of the statistics curriculum—the set of topics students are supposed to learn in STATS 101. I’ll list all the topics of the “classical” curriculum based on analytical approximations like the t-test. This is the approach currently taught in most high schools and universities around the world.

The “classical” curriculum has a number of problems with it. The main problem is that it’s based on difficult to understand concepts, and these concepts are often presented as procedures to follow without understanding the details. The classical curriculum is also very narrow, since it covers a slim subset of all the possible types of statistical analysis that can be described as math formulas that can be used blindly by plugging in the numbers. In the end of the introductory stats course, students know a few “recipes” for statistical analysis they can apply if they ever run into one of the few scenarios where the recipe can be used (comparison of two proportions, comparison of two means, etc.). That’s nice, but in practice this leaves learners totally unprepared to solve all stats problems that don’t fit the memorized templates, which is most of the problems they will need to solve in their day-to-day life. The current statistics curriculum is simply outdated (developed in times when the only computation available was simple algebraic formulas for computing test statistics and lookup tables for finding p-values). The focus on formulas and use of analytical approximations in the classical curriculum limits learners development of adjacent skills like programming and data management. Clearly there is room for improvement here, we can’t let the next generation of scientists, engineers, and business folks grow up without basic data literacy.

Something must be done.

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Multilingual authoring for the win

I have been working on a French translation for the math book and in the process I stumbled upon some really powerful “authoring hacks” that I would like to describe here in case they might be useful for other bilingual authors and educators.

Let’s see les maths!

Before we begin with the “How it’s made” episode, let me show you some examples of the final product. I have selected the best four “backports” — explanations that now exist in the English version thanks to the additions in the French version.

  1. Reader feedback was consistent at pointing out the algebra sections as boring and TL;DR. Readers are willing to learn algebra (the rules for manipulating math expressions), but then when it comes to algebra “techniques” they are not sold on the concept. One solution to this problem would be to drop the “boring stuff” (lower the expectations of the reader), but I was having none of this. Instead I decided to just improve the explanations and add pictures: Completing the square en Français et in English.
  2. Functions (modelling superpowers) are the best thing ever, and probably the most powerful tool readers will develop in the book. This is why proper definitions and examples of functions are essential.
  3. Polar coordinates are super important—for both practical reasons and for the “aha” moment (knowledge buzz) that occur when readers understand $(x,y)$ is just one example of the many possible representations of the points in the Cartesian plane and $r\angle \theta$ is an equivalent representation (instructions that specify the position of a particular point int he Cartesian plane based on the distance $r$ and direction $\theta$).
  4. Speaking of knowledge buzz through representation theory, the book now finally has a proper motivation why readers need to think about the concept of a basis (a set of direction vectors that is used as the coordinate system for a vector space). On this one I go back to the basics—explain through an example.

Contuinuez à lire si ça a l’air intéressant. Read on if you’re interested.

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Impression from NYC and the RC

Two months ago I was on a train going from Montreal to New York City. It’s a long ride, but I used the time on the train to triage all the coding project ideas I could work on while at the Recurse Center (RC). So many projects; so many ideas.

Today I’m on the same train heading back to Montreal and have another 10 hours to triage the thoughts, experiences, and observations about the big city and the social experiment that is RC. Here is my best shot at it—stream-of-consciousness-style—before I forget it all.

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The textbook business

This is a followup on my previous post about the challenges of open educational resources (OER) production and adoption. I’ve come to the conclusion that the key aspect holding back the “OER dream” is not the lack of collaboration tools or the ability for teachers to discover material, but the quality of the content. You can’t write a textbook by committee. It’s as simple as that!

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Improving the math chapter

The goal for the NO BULLSHIT guide to MATH & PHYSICS was to make a concise textbook that teaches university-level calculus and mechanics in a nice “combined package.” The math fundamentals chapter grew out of the need to introduce the prerequisite material that many students often lack. I didn’t want to be like “y’all should remember this math from high school,” because if you don’t remember the material such comments would not be very helpful. A review of high school math would be more helpful.

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The aims of education according to Alfred North Whitehead

Yesterday I read the fascinating essay titled The Aims of Education by Alfred North Whitehead (1861-1947). It was written 100 years ago, but every line of it rings true in the modern context. Below I’ve extracted the best quotes from the essay and added some personal comments.

The OP gives a detailed blueprint of how to structure formal education, making a distinction between “general education” (primary school and middle school) and “specialized training” (high school and college). The essay discusses learner psychology, learner user experience, curriculum customization, student assessment, and even proposes a new structure for the educational system. The essay is so full of good stuff that nearly all of it is worth quoting.

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Learning can be fun

I just read this excellent article Pragmatic Learning: It’s not “fun” on Roger Schank’s blog. It’s a very good post that calls bullshit on the “gamification” cargo cult which is widespread in the edtech and corporate training world. Just adding points, badges, and levels to a corporate training program that teaches you something boring is not going to suddenly make it fun. The author’s main observation is that forced learning is not fun and we need not pretend it is. Consider an employer who wants their employees to know X because it is required by law, or a bunch of students forced to learn Y or else they’ll fail. These “forced” trainings are not fun, and gamifying them is akin to putting lipstick on a pig.

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The school of the future

It has been a long time since I last wrote something, but I haven’t been idle altogether. I’ve been planning what to do next for the books, calculating my move, so to say. It’s slowly starting to become clearer. Given my background as linux sysadmin and tutor, it only makes sense if the revolution looks to me like an open source software stack for schools. Read on to find the general strategy. Listen to this good tune if you’re missing an accompanying soundtrack; here is some more tunes in case the blog post ends up long.

I’m going to write a toolbox for every school out there to print their own textbooks and other educational material.

The best-in-class existing exercise framework is already available as open source and can be hosted on the school’s server (or virtual on AWS for $40/mo), but since we’re going to have a “school server,” wouldn’t we want to run some other stuff on there too?

I’m thinking:

  • printable exercises sheets for doing in class
  • printable problems to give as homework
  • printable exams (different version for each student)
  • print affordable textbooks (using POD service like lulu.com)

I’m happy for all the kids with iPods and computers at home, but not every school has the budget for computers, so let’s try to keep the costs to at most $20 per class for the week. A few good laser printers could keep the school running with students learning from top notch material, at the cost of a few thousand dollars per month. Toner and paper.

Okay, but where are you going to get the content.

There’s plenty of OER out there, but there could be more and it could be made more easily accessible.

Content framework

Here I must confess, I will be biased, because as a django person, I see the world through my own prism. A very good way for presenting structured content exists already, as free software. That’s the best place to start. Everything else on the content management side, and exporting printable PDFs I can script myself. The main content pipeline will be something like .md --> .tex --> .pdf; the softcover/polytexnic toolchain is very good at this.

UX

The key is to make it easy for teachers to browse, use, and contribute content. The graph structure (and possible common core math categorization) will help the browsing, the .toPDF() methods will make the content immediately usable, and the only real problem remaining is the user experience that entices teachers to contribute content. That’s the biggie. But it can be done.

Software requirement specification

Given a collection of content items (paragraphs of text, entire sections of book, exercises, or problems), the system allows teachers to assemble custom “playlists” which consists of a sequence of content items with a `.toPDF` method.

No way I’m going to let them run the high schools. We’re taking over that business too now.

Aren’t big publishers better?

The market forces will prevail. What is better for a cash-strapped school, to order some crusty mainstream algebra textbook, that may or may not be standard-compliant, but sure is long and talks to students as retards, or to demand the printing of one copy of the best free book on the subject, for 1/10 of the cost.

How will you make money?

Nothing changes really. Minireference continues to sell university-level textbooks; we just make the high school material and the toolchain free. As for the potential loss of business due to high schools printing on their own instead of buying textbooks from me, I’d call that a win overall.