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I like the inclusion of randomization and bootstrapping. It's unfortunate that the hypothesis framework is still NHST -- I wouldn't consider that 'modern' by an

I like the inclusion of randomization and bootstrapping. It's unfortunate that the hypothesis framework is still NHST -- I wouldn't consider that 'modern' by any means.

noelwelsh 3y ago
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 to students to not introduce them.
- begemotz 3y ago
  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 And in that context, there is a lot of agreement that this approach is fundamentally flawed and outdated.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. But off the top of my head consider Gigerenzer and Cummings.
  - noelwelsh 3y ago
    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_2101335/content https://pure.mpg.de/rest/items/item_2101336/component/file_2... [2]: Sample at https://tandfbis.s3.amazonaws.com/rt-media/pp/common/sample-chapters/9780415879682.pdf https://tandfbis.s3.amazonaws.com/rt-media/pp/common/sample-...
    - begemotz 3y ago
      Yes, those are appropriate (although Gigerenzer and Cummings both have other relevant publications on the topic). As for a undergraduate text that 'teaches the difference', you can look at 'An Introduction to Statistics' by Carlson & Winquist.

I like the inclusion of randomization and bootstrapping. It's unfortunate that the hypothesis framework is still NHST -- I wouldn't consider that 'modern' by any means.

noelwelsh 3y ago

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 to students to not introduce them.

begemotz 3y ago
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. But off the top of my head consider Gigerenzer and Cummings.
- noelwelsh 3y ago
  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_2101335/content https://pure.mpg.de/rest/items/item_2101336/component/file_2... [2]: Sample at https://tandfbis.s3.amazonaws.com/rt-media/pp/common/sample-chapters/9780415879682.pdf https://tandfbis.s3.amazonaws.com/rt-media/pp/common/sample-...
  - begemotz 3y ago
    Yes, those are appropriate (although Gigerenzer and Cummings both have other relevant publications on the topic). As for a undergraduate text that 'teaches the difference', you can look at 'An Introduction to Statistics' by Carlson & Winquist.