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Inappropriate sampling, which limits the scope of valid inferences, and the ability to detect true effects in one’s data.
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A wide-spread misuse of the null hypothesis significance testing paradigm, which ultimately does not lend itself to the answering of scientific questions.
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Poor operationalization of hypotheses, which leads to unjustified generalisations.
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A lack of overarching theoretical frameworks or cumulative theory-building, which means research programs are conceived and pursued unconstrained.
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Knowledge gained in one class was rarely, if ever, useful in another class.
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Lectures were a seemingly arbitrary hodgepodge of empirical findings.
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Assignments could be bluffed because in many cases markers cannot really evaluate the validity of your claims, and instead award points based on your ability to reproduce patterns of criticism (e.g., “this study had a small sample size”, “this finding is not cross-cultural”, “this design did not account for factor f”). Perhaps it was no coincidence, then, that assignment feedback was almost always generic.
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The methodological issues in the field were not given their due diligence, not even at a graduate-level statistics seminar I audited.
Last reply 11 hours ago
Wolverhampton MSc psychology mental health and well-being (online)132
Last reply 11 hours ago
Wolverhampton MSc psychology mental health and well-being (online)132