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Is there already a paragraph or two in the book about hypothesis testing, and the fact that these statistical tests only make sense with a priori hypotheses? I assume there will be a discussion about inference vs exploratory analyses later on but it would not harm to mention that these tests test one a priori defined hypothesis here already.
Also, I would add somewhere in this chapter an explanation of why this approach uses null hypothesis testing (i.e., the only hypothesis for which we have some information)
PS I don't understand the last sentence from Audrey.
Add a box on a one-sided t-test.
Relocate funnel plot to beginning of discussion on Type M and S errors.
Explain Levy and Keller design (2.7.1) in more detail. The word adjunct was not clear to Audrey.
When showing the formant data (Apache etc), show more than one vowel.
Explain what degrees of freedom is
Add a section on why aggregation is bad.
The text was updated successfully, but these errors were encountered:
Is there already a paragraph or two in the book about hypothesis testing, and the fact that these statistical tests only make sense with a priori hypotheses? I assume there will be a discussion about inference vs exploratory analyses later on but it would not harm to mention that these tests test one a priori defined hypothesis here already.
Also, I would add somewhere in this chapter an explanation of why this approach uses null hypothesis testing (i.e., the only hypothesis for which we have some information)
PS I don't understand the last sentence from Audrey.
The text was updated successfully, but these errors were encountered: