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11 votes
Accepted

Variance of Estimator in Casella and Berger

From the way that passage of the book is set up, it seems they want us to think of the estimator $X-\frac{1}{2} + \frac{\sin(2\pi X)}{2\pi}$ as a linear combination of the ``naive" estimator $A = ...
John Madden's user avatar
  • 4,355
2 votes

Within subject experiments done by (some) Psychologists

Talking about the definition of the term "experiment", I think it is fulfilled if they first have a research hypothesis, and then what they run is planned in such a way that they can control ...
Christian Hennig's user avatar
2 votes

Is there just one exponential family? Or are there many exponential families?

Possibly a reason for the confusing terminology is that 'the exponential family' is a family of families $f(x|\theta)$ *. Why the name 'exponential'? Each of the families has the property that it can ...
Sextus Empiricus's user avatar
2 votes

How to interpret a QQ plot?

In addition to nice explanations above, I put a snippet generating a nice gallery of (pretty much) self-explanatory examples that I found useful when teaching university classes in statistics. ...
Maciej Skorski's user avatar
1 vote

What statistical tests to use for multiple datasets?

So you data is something like this/could be arranged like this? ...
Sointu's user avatar
  • 1,978
1 vote
Accepted

Inference from profile comparisons

You have compositional data, you can peruse the tag compositional-data at site. You can use some transforms to help in analysis, see a summary here. Some useful posts on this site to get you started: ...
kjetil b halvorsen's user avatar
1 vote

Correct interpretation of an Unbiased Test

To ensure that $\beta(\theta_1) \geq \beta(\theta_0)$ for all $\theta_1 \in \Theta_{0}^{\complement}, \theta_0 \in \Theta_{0}$, it suffices to check that the inequality holds when the LHS is minimised ...
Doctor Milt's user avatar
  • 3,231
1 vote

Causal inference and Propensity score

Strictly speaking propensity score (PS) analysis is not a causal method. It is just a “confounder concentrator” or data reduction method. It allows you to use fewer parameters in the outcome model ...
Frank Harrell's user avatar

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