Name: Exploratory data analysis
ISBN: 9780201076165

What Hacker News says

constantinumMay 2024

Exploratory Data Analysis (Pearson Modern Classic) by John W. Tukey

thread

yesenadamJan 2023

Gauss invented FFT, in 1805. And "Between 1805 and 1965, some versions of FFT were published by other authors"

https://en.wikipedia.org/wiki/Fast_Fourier_transform#History

p.s. I started reading Tukey's textbook Exploratory Data Analysis just yesterday. It's wonderful so far, a pleasure to read. "It is important to understand what you CAN DO before you learn to measure how WELL you seem to have DONE it." "The greatest value of a picture is when it forces us to notice what we never expected to see."

thread

madhadronJun 2022

I really wish that I had something comprehensive to suggest. There are some things that I think everyone who deals with statistics should read, such as Freedman's 'Statistical Models and Shoe Leather'[^1] and Tukey's 'Exploratory Data Analysis'[^2]. Pearl's 'Causal Inference in Statistics' is the best introduction I know of to issues of causality as we understand them today. For actual inference, the basis is one player game theory (aka, decision theory). I learned it from Kiefer's 'Introduction to Statistical Inference,' which sets out the theory very nicely in the first few chapters. That's a starting point at least. There are some interesting courses[^3] that try to teach statistics via resampling that seem pedagogically very valuable. Resampling does build intuition nicely and using it gets people over their squeamishness around using randomized procedures.

[^1]: http://psychology.okstate.edu/faculty/jgrice/psyc5314/Freedm...

[^2]: Sadly really hard to find. We need a cheap reprint of this.

[^3]: https://resample.statistics.com/intro-text-online/

thread

sevensorMay 2017

Learn math, and everything else in life gets easier, including programming. We did a quick proof about similar triangles on the whiteboard this morning and it saved us a bunch of effort. Learn programming, and you can automate some stuff that's too laborious to do by hand. I say, learn math first, then learn programming. Otherwise you're bound to spend your days automating the wrong thing. For programming statistics, I'd spend some time with Tukey's Exploratory Data Analysis before writing any code. It's pretty amazing what you can do with pen and paper.

thread

2b3a51May 2026

The list of books was welcome, and the work is impressive. I always made do with section pad and a hard pencil and a simple stencil, but it wasn't for camera ready publication use or anything. Just visualisation and discussion.

My book suggestion is more illustration than technical drawing but still has a 1940s/50s vibe: Thinking with a Pencil by Henning Helms. Covers illustrations, tracing, tables, maps and diagrams as well as 3d sketches.

I gather that Tufte was influenced by John Tukey's 1977 book Exploratory Data Analysis which introduces the box and whisker plot, dot plot and so on.

As to software, another poster has mentioned Tikz (usually used with LaTeX) and yes it is amazingly flexible and can produce just about any kind of plot (or diagram) you want. But there are older tools such as the groff (GNU Troff) system's pic and a pre-processor for pic called grap which is much more barebones. The latter was also influenced by Tukey's book. The groff/pic/tbl/eqn/grap install is something like 30Mb and it is available in most Linux distribution package repositories.

https://www.lunabase.org/~faber/Vault/software/grap/example/

Oh and remember star charts for astronomers! Many hand plotted before the photographic surveys were produced. Norton's Star Atlas is a famous one (prior to the 2000.0 epoch edition) that was hand drawn.

thread

ehw3Jul 2021

> 2. John Tukey (1977). Exploratory Data Analysis.

> This book has been hugely influential and is a fun read that can be digested in one sitting.

Wow. The PDF is over 700 pages. That seems fairly impressive for single-sitting digestion.

thread