Question: ReflEctive statement on p-values Refective starement For this assignment you need to read three papers.The first paper you need to read is Wasserstein and Lazar

ReflEctive statement on p-values

Refective starement

For this assignment you need to read three papers.The first paper you need to read is Wasserstein and Lazar (2016). This very short piece sets the context for the remaining papers that you will read.This paper has been added to the LMS.For the remaining papers, you have a choice. You are to select any two papers from the American Statistician Special Issue: Statistical Inference in the 21st Century: A World Beyond P<0.05, which can be found at the following link: https://www.tandfonline.com/toc/utas20/73/sup1?nav=tocList.The set of papers in the journal reflect heterogeneity in views. This makes it challenging to draw lessons from the literature, but that is the task you have been set.

Your reflective statement should be around 500 words. In the statement you should first describe the key message from the two papers that you have selected as your focus papers from the special issue.In your reflective statement, make it clear which message is associated with each paper, by referencing the paper appropriately. Note, you do not need to summarise the Wasserstein and Lazar (2016) statement. Once you have described the key message of each paper, you then need to describe how the key message from the paper will impact the way you work on future questions that involve statistical analysis. To develop an integrated statement, where you can match the message from the paper to the type of work you might actually do in the future, it is likely you will need to look at more than two papers from the special issue. I recommend first skimming several papers to see which ones are of interest to you, and which papers are relevant for the context you are most familiar with, and then selecting two papers to focus on.

Marking

The Assignment weight is as per the Unit Outline, but the assignment will be market out of 10.

References

Wasserstein, R. L., & Lazar, N. A. (2016). The ASA's statement on p-values: context, process, and purpose. The American Statistician, 70(2), 129-133.

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