Ethics in Stats

Week 4 Discussion #ethicsinstats What role does researcher bias play in the interpretation of analyses? Why is this an ethical concern for researchers and is there any way around it? Give your post a hashtag (for example, #statsskew). Which outside resource (image, video, article) gives a great example of researcher bias? Share the link within your post. What struck you most about this example? What about this week's content is relevant to your own professional or academic career? Researcher bias can play a role in the interpretation of analysis accidentally or purposely. This can pose ethical concerns in research, however, it may not always be evident if the bias is unintentional or intentional. When interpreting data, specifically data sets with outlier, multiple, or confounding variables, researchers may conclude different interpretations. In our applied statistics textbook, grumpiness is measured on a numerical scale and correlated with hours of sleep per night (Warner, 2021). Grumpiness is a mood that does not omit numerical outcomes unless gauged with an opinion-based ranking system. When interpreting data in more formal settings, administering proper training and testing to researchers may decrease bias. Warner, R. M. (2021). Applied statistics I: Basic bivariate techniques (3rd ed.). Sage. Chapter 11, "Correlation and Linear Regression [PDF]."
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