Thanks to the author for the book and making it open access. I always admire these efforts.
Introduction to Modern Statistics
41–50 of 138 posts
Re: Introduction to Modern Statistics
#42[dead]
Re: Introduction to Modern Statistics
#43What's often missing from these introductions is when statistics will not work; and what it even means when it "works". The amount of data needed to tell between two normal is about 30 data points -- between two power-law distributions, >trillion. (And this basically scuppers the central limit theorem, on which a lot of cargo-cult stats is justified). Stats, imv, should be taught simulation-first: code up your hypoth…
I work in applied ML and stats. Whenever a client gets pushy about getting a prediction and would not care about quantifying the uncertainty around it, I take it as a signal to disengage and look for better pastures. It is really not worth the time, more so if you value integrity.
Competent stakeholders and decision makers use the uncertainty around predictions, the chances of an outcome that is different from the point-predicted outcome, to come to a decision and the plan includes what the course of action should be should the outcome differ from the prediction.
Re: Introduction to Modern Statistics
#44What's often missing from these introductions is when statistics will not work; and what it even means when it "works". The amount of data needed to tell between two normal is about 30 data points -- between two power-law distributions, >trillion. (And this basically scuppers the central limit theorem, on which a lot of cargo-cult stats is justified). Stats, imv, should be taught simulation-first: code up your hypoth…
It's ironic that this ... rant? ... is basically unreadable without knowledge of basic statistical methods. How do you teach any of this to someone who hasn't already taken introductory statistics? How do you learn anything if you first have to learn the myriad ways something you don't even have a basic working knowledge of can fail before you learn it?
It seems like a reasonable critique. The suggestion is to include such ideas as people are taking introductory statistics which isn’t inappropriate. I wouldn’t suggest forcing students to code up their own simulations from scratch, but creating a framework where students can plug in various formula for each population, attach a statistical test, and then run various simulations could do quite a bit. However, what kinds of formula students are told to plug in are important.
If every formula is producing bell curves then that’s a failure to educate people. 50d6 vs 50d6 + 1 is easy enough you can include 1d2 * 50 + 50d6 for a 2 tailed distribution, but also significantly different distributions which then fail various tests etc.
I’ve seen people correctly remember the formula for statistical tests from memory and then wildly misapply them. That seems like focusing on the wrong things in an age when such information is at everyone’s fingertips, but understanding of what that information means isn’t.
Re: Introduction to Modern Statistics
#45What is a good book on statistics that one can use for self-learning?
I particularly like Statistical Inference by George Casella and Roger Lee Berger. You could also look at Introduction to Probability by Joseph K. Blitzstein and Jessica Hwang (available for free here: http://probabilitybook.net (redirects to drive)).
Should be noted that Casella’s book is… well… really great if you thought Spivak’s calculus and Rudin’s analysis to be fun books, especially the exercises.
Casella’s exercises are absolutely brutal.
Re: Introduction to Modern Statistics
#46Is there a "pre-statistics" book that teaches the thinking skills and concepts needed to understand statistics?
Re: Introduction to Modern Statistics
#47Is there a "pre-statistics" book that teaches the thinking skills and concepts needed to understand statistics?
This book seems to start where you need it to start.
You don't need much beyond basic calculus. Most suffer from some mental block they got installed at a young age akin those that say "I'm bad at math" because their teacher sucked. Dive in and you won't regret it.
Re: Introduction to Modern Statistics
#48Re: Introduction to Modern Statistics
#49Earlier quoted context omitted.
I don't see widespread agreement in the statistics community as to what should replace NHST. If you go Bayesian you need to completely rewrite the course. I've seen confidence intervals suggested as an alternative, but there are arguments against. I've also seen arguments that hypothesis tests shouldn't be used at all. Given that NHST is still widely used and there isn't a clear alternative I think it's a disservice…
I probably should have been more clear. I didn't say hypothesis testing, I said NHST (the binary null/alt hypothesis approach) - which is an approach to hypothesis testing particularly prevelant in certain disciplines such as Psychology. And in that context, there is a lot of agreement that this approach is fundamentally flawed and outdated. if you are interested, I can provide references when I get to the office. Bu…
For those following along at home Gigerenzer is, I think, "Mindless Statistics"[1] and Cummings is "The New Statistics"[2].
[1]: https://pure.mpg.de/rest/items/item_2101336/component/file_2... [2]: Sample at https://tandfbis.s3.amazonaws.com/rt-media/pp/common/sample-...
Re: Introduction to Modern Statistics
#50One of my favourite books on statistics and probability is "Regression and Other Stories", by Andrew Gelman, Jennifer Hill and Aki Vehtari. You can access the book for free here: https://users.aalto.fi/~ave/ROS.pdf