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1500 questions
43
votes
1 answer
Maximum likelihood estimators for a truncated distribution
Consider $N$ independent samples $S$ obtained from a random variable $X$ that is assumed to follow a truncated distribution (e.g. a truncated normal distribution) of known (finite) minimum and maximum values $a$ and $b$ but of unknown parameters…
a3nm
- 707
43
votes
7 answers
How often do you have to roll a 6-sided die to obtain every number at least once?
I've just played a game with my kids that basically boils down to: whoever rolls every number at least once on a 6-sided die wins.
I won, eventually, and the others finished 1-2 turns later. Now I'm wondering: what is the expectation of the length…
Jonas
- 1,678
43
votes
3 answers
How to determine the quality of a multiclass classifier
Given
a dataset with instances $x_i$ together with $N$ classes where every instance $x_i$ belongs exactly to one class $y_i$
a multiclass classifier
After the training and testing I basically have a table with the true class $y_i$ and the…
Gere
- 2,061
43
votes
8 answers
How do I get people to take better care of data?
My workplace has employees from a very wide range of disciplines, so we generate data in lots of different forms. Consequently, each team has developed its own system for storing data. Some use Access or SQL databases; some teams (to my horror)…
Richie Cotton
- 684
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- 16
43
votes
2 answers
What is the difference between the Shapiro–Wilk test of normality and the Kolmogorov–Smirnov test of normality?
What is the difference between the Shapiro–Wilk test of normality and the Kolmogorov–Smirnov test of normality? When will results from these two methods differ?
russellpierce
- 18,599
43
votes
3 answers
What test can I use to compare slopes from two or more regression models?
I would like to test the difference in response of two variables to one predictor. Here is a minimal reproducible example.
library(nlme)
## gls is used in the application; lm would suffice for this example
m.set <- gls(Sepal.Length ~ Petal.Width,…
Abe
- 3,811
43
votes
1 answer
What is the difference between "coefficient of determination" and "mean squared error"?
For regression problem, I have seen people use "coefficient of determination" (a.k.a R squared) to perform model selection, e.g., finding the appropriate penalty coefficient for regularization.
However, it is also common to use "mean squared…
dolaameng
- 533
43
votes
9 answers
Correlation does not imply causation; but what about when one of the variables is time?
I know this question has been asked a billion times, so, after looking online, I am fully convinced that correlation between 2 variables does not imply causation. In one of my stats lectures today, we had a guest lecture from a physicist, on the…
Thomas Moore
- 1,695
43
votes
8 answers
When should one include a variable in a regression despite it not being statistically significant?
I am an economics student with some experience with econometrics and R. I would like to know if there is ever a situation where we should include a variable in a regression in spite of it not being statistically significant?
EconJohn
- 882
43
votes
4 answers
What exactly is the difference between a parametric and non-parametric model?
I am confused with the definition of non-parametric model after reading this link Parametric vs Nonparametric Models and Answer comments of my another question.
Originally I thought "parametric vs non-parametric" means if we have distribution…
Haitao Du
- 36,852
- 25
- 145
- 242
43
votes
5 answers
Neural network references (textbooks, online courses) for beginners
I want to learn Neural Networks. I am a Computational Linguist. I know statistical machine learning approaches and can code in Python.
I am looking to start with its concepts, and know one or two popular models which may be useful from a…
HIGGINS
- 509
43
votes
1 answer
Step-by-step example of reverse-mode automatic differentiation
Not sure if this question belongs here, but it's closely related to gradient methods in optimization, which seems to be on-topic here. Anyway, feel free to migrate if you think some other community has better expertise in the topic.
In short, I'm…
ffriend
- 9,990
43
votes
3 answers
Why is the mean function in Gaussian Process uninteresting?
I have just started reading about GPs and analogous to the regular Gaussian distribution it is characterized by a mean function and the covariance function or the kernel. I was at a talk and the speaker said that the mean function is usually quite…
Luca
- 4,650
43
votes
1 answer
Bootstrapping vs Bayesian Bootstrapping conceptually?
I'm having a trouble understanding what a Bayesian Bootstrapping process is, and how that would differ from your normal bootstrapping. And if someone could offer an intuitive/conceptual review and comparison of both, that would be great.
Let's take…
SpicyClubSauce
- 565
43
votes
1 answer
Doing principal component analysis or factor analysis on binary data
I have a dataset with a large number of Yes/No responses. Can I use principal components (PCA) or any other data reduction analyses (such as factor analysis) for this type of data? Please advise how I go about doing this using SPSS.
Cathy
- 431