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Archive of posts filed under the Miscellaneous Statistics category.

Solution to the sample-allocation problem

See this recent post for background. Here’s the question: You are designing an experiment where you are estimating a linear dose-response pattern with a dose that x can take on the values 1, 2, 3, and the response is continuous. Suppose that there is no systematic error and that the measurement variance is proportional to x. You […]

Solution to the problem on the distribution of p-values

See this recent post for background. Here’s the question: It is sometimes said that the p-value is uniformly distributed if the null hypothesis is true. Give two different reasons why this statement is not in general true. The problem is with real examples, not just toy examples, so your reasons should not involve degenerate situations such as […]

Solution to the helicopter design problem

See yesterday’s post for background. Here’s the question: In the helicopter activity, pairs of students design paper ”helicopters” and compete to create the copter that takes longest to reach the ground when dropped from a fixed height. The two parameters of the helicopter, a and b, correspond to the length of certain cuts in the […]

Some questions from our Ph.D. statistics qualifying exam

In the in-class applied statistics qualifying exam, students had 4 hours to do 6 problems. Here were the 3 problems I submitted: In the helicopter activity, pairs of students design paper ”helicopters” and compete to create the copter that takes longest to reach the ground when dropped from a fixed height. The two parameters of the […]

Hoe noem je?

Haynes Goddard writes: Reviewing my notes and books on categorical data analysis, the term “nominal” is widely employed to refer to variables without any natural ordering. I was a language major in UG school and knew that the etymology of nominal is the Latin word nomen (from the Online Etymological Dictionary: early 15c., “pertaining to […]

The Fault in Our Stars: It’s even worse than they say

In our recent discussion of publication bias, a commenter link to a recent paper, “Star Wars: The Empirics Strike Back,” by Abel Brodeur, Mathias Le, Marc Sangnier, Yanos Zylberberg, who point to the notorious overrepresentation in scientific publications of p-values that are just below 0.05 (that is, just barely statistically significant at the conventional level) […]

I didn’t say that! Part 2

Uh oh, this is getting kinda embarrassing. The Garden of Forking Paths paper, by Eric Loken and myself, just appeared in American Scientist. Here’s our manuscript version (“The garden of forking paths: Why multiple comparisons can be a problem, even when there is no ‘fishing expedition’ or ‘p-hacking’ and the research hypothesis was posited ahead […]

When there’s a lot of variation, it can be a mistake to make statements about “typical” attitudes

This story has two points: 1. There’s a tendency for scientific results to be framed in absolute terms (in psychology, this corresponds to general claims about the population) but that can be a mistake in that sometimes the most important part of the story is variation; and 2. Before getting to the comparisons, it can […]

“We have used Stan to study dead dolphins”

In response to our call for references to successful research using Stan, Matthieu Authier points us to this: @article{ year={2014}, journal={Biodiversity and Conservation}, volume={23}, number={10}, doi={10.1007/s10531-014-0741-3}, title={How much are stranding records affected by variation in reporting rates? A case study of small delphinids in the Bay of Biscay}, url={http://dx.doi.org/10.1007/s10531-014-0741-3}, keywords={Monitoring; Marine mammal; Strandings}, author={Authier, Matthieu […]

Anova is great—if you interpret it as a way of structuring a model, not if you focus on F tests

Shravan Vasishth writes: I saw on your blog post that you listed aggregation as one of the desirable things to do. Do you agree with the following argument? I want to point out a problem with repeated measures ANOVA in talk: In a planned experiment, say a 2×2 design, when we do a repeated measures […]