5 Ways To Overcome Junk Data From mTurk (and online surveys more generally)

The data quality on Amazon Mechanical Turk (mTurk) has suffered for years now (Byrd, 2023; Chandler & Paolacci, 2017; Moss & Litman, 2018; Chmielewski & Kucker, 2019; Ahler et al., 2020; Kennedy et al., 2020; MacInnis et al., 2020). There are a few ways to protect online survey data quality. In this post, I will briefly cover five strategies for weeding out junk data in online research (not just via mTurk), from easiest to hardest.

(Note: The featured image at the top is based on data from this paper in Analysis. We deploy these and other data quality methods in this paper in Religious Studies and this preprint. )

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The meaning of ‘statistical significance’ and of p-values

A 2019 paper in the Advances in Methods and Practices in Psychological Science found that most psychology textbooks, instructors, and students misinterpret ‘statistical significance’ and p-values. Talk about a headline! More important than the headline, however, are the right interpretations and what we can do to correct widespread misinterpretations. In this post, I explain the authors’ findings and the three solutions they propose.

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