Lakens / statistical_inferences

Repository for the textbook 'Improving Your Statistical Inferences' by Daniel Lakens
https://lakens.github.io/statistical_inferences
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Update 09-equivalencetest.Rmd #39

Closed halseylg closed 2 years ago

Lakens commented 2 years ago

This is absolutely amazing - this chapter was a bit of a mess (someone actually complained about it yesterday!) and you fixed so many errors - I could not be more grateful. Thanks you!

The section on equivalence tests, is about equivalence tests. The only difference is the reversal of what is H1 and H0 -in an equivalence test, we aim to REJECT effects large enough to be meaningful. So, the H0 is the effect is large enough to matter - and H1 is we expect the effect is close to 0. So, unless I misunderstood the comment, the heading is correct.

Thanks again - this kind if helpful contributions, exactly at the right time, warms my heart, and convinces me even more that open access publishing was the right choice.

halseylg commented 2 years ago

Hi Daniel,

Well, I can certainly say that the open accessing publishing of your book has been great for me at least!

I admit that getting my head around equivalence tests is tricky, but I guess it just takes time. It might be possible to further annotate the figures and/or increase the text in the figure captions for this chapter, but of course it's always possible to add more and then there is the risk of too much information. Always a tricky balance.

I look forward to reading the next chapter...

From: Daniel Lakens @.> Sent: 31 May 2022 20:21 To: Lakens/statistical_inferences @.> Cc: Lewis Halsey @.>; Author @.> Subject: Re: [Lakens/statistical_inferences] Update 09-equivalencetest.Rmd (PR #39)

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This is absolutely amazing - this chapter was a bit of a mess (someone actually complained about it yesterday!) and you fixed so many errors - I could not be more grateful. Thanks you!

The section on equivalence tests, is about equivalence tests. The only difference is the reversal of what is H1 and H0 -in an equivalence test, we aim to REJECT effects large enough to be meaningful. So, the H0 is the effect is large enough to matter - and H1 is we expect the effect is close to 0. So, unless I misunderstood the comment, the heading is correct.

Thanks again - this kind if helpful contributions, exactly at the right time, warms my heart, and convinces me even more that open access publishing was the right choice.

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