Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Most Popular

more tags
1500 questions
73
votes
5 answers

Is it true that the percentile bootstrap should never be used?

In the MIT OpenCourseWare notes for 18.05 Introduction to Probability and Statistics, Spring 2014 (currently available here), it states: The bootstrap percentile method is appealing due to its simplicity. However it depends on the bootstrap…
Clarinetist
  • 4,977
73
votes
11 answers

Having a job in data-mining without a PhD

I've been very interested in data-mining and machine-learning for a while, partly because I majored in that area at school, but also because I am truly much more excited trying to solve problems that require a bit more thought than just programming…
Charles Menguy
  • 2,367
73
votes
7 answers

Why is the validation accuracy fluctuating?

I have a four layer CNN to predict response to cancer using MRI data. I use ReLU activations to introduce nonlinearities. The train accuracy and loss monotonically increase and decrease respectively. But, my test accuracy starts to fluctuate wildly.…
pseudomonas
  • 853
  • 1
  • 8
  • 10
73
votes
3 answers

Is this the solution to the p-value problem?

In February 2016, the American Statistical Association released a formal statement on statistical significance and p-values. Our thread about it discusses these issues extensively. However, no authority has come forth to offer a universally…
whuber
  • 322,774
73
votes
15 answers

Complete substantive examples of reproducible research using R

The Question: Are there any good examples of reproducible research using R that are freely available online? Ideal Example: Specifically, ideal examples would provide: The raw data (and ideally meta data explaining the data), All R code including…
Jeromy Anglim
  • 44,984
73
votes
5 answers

Why do we minimize the negative likelihood if it is equivalent to maximization of the likelihood?

This question has puzzled me for a long time. I understand the use of 'log' in maximizing the likelihood so I am not asking about 'log'. My question is, since maximizing log likelihood is equivalent to minimizing "negative log likelihood" (NLL), why…
Tony
  • 1,803
73
votes
4 answers

Logistic Regression - Error Term and its Distribution

On whether an error term exists in logistic regression (and its assumed distribution), I have read in various places that: no error term exists the error term has a binomial distribution (in accordance with the distribution of the response…
user61124
  • 733
73
votes
4 answers

Assumptions regarding bootstrap estimates of uncertainty

I appreciate the usefulness of the bootstrap in obtaining uncertainty estimates, but one thing that's always bothered me about it is that the distribution corresponding to those estimates is the distribution defined by the sample. In general, it…
user4733
  • 2,714
73
votes
3 answers

What does standard deviation tell us in non-normal distribution

In a normal distribution, the 68-95-99.7 rule imparts standard deviation a lot of meaning, but what would standard deviation mean in a non-normal distribution (multimodal or skewed)? Would all data values still fall within 3 standard deviations? Do…
Zuhaib Ali
  • 831
72
votes
3 answers

A generalization of the Law of Iterated Expectations

I recently came across this identity: $$E \left[ E \left(Y|X,Z \right) |X \right] =E \left[Y | X \right]$$ I am of course familiar with the simpler version of that rule, namely that $E \left[ E \left(Y|X \right) \right]=E \left(Y\right) $ but I was…
JohnK
  • 20,366
72
votes
3 answers

Why is logistic regression a linear classifier?

Since we are using the logistic function to transform a linear combination of the input into a non-linear output, how can logistic regression be considered a linear classifier? Linear regression is just like a neural network without the hidden…
Jack Twain
  • 8,381
72
votes
7 answers

Data normalization and standardization in neural networks

I am trying to predict the outcome of a complex system using neural networks (ANN's). The outcome (dependent) values range between 0 and 10,000. The different input variables have different ranges. All the variables have roughly normal…
Boris Gorelik
  • 2,707
72
votes
8 answers

Is PCA followed by a rotation (such as varimax) still PCA?

I have tried to reproduce some research (using PCA) from SPSS in R. In my experience, principal() function from package psych was the only function that came close (or if my memory serves me right, dead on) to match the output. To match the same…
Roman Luštrik
  • 3,718
72
votes
18 answers

Statistics interview questions

I am looking for some statistics (and probability, I guess) interview questions, from the most basic through the more advanced. Answers are not necessary (although links to specific questions on this site would do well).
shabbychef
  • 14,814
72
votes
9 answers

Which pseudo-$R^2$ measure is the one to report for logistic regression (Cox & Snell or Nagelkerke)?

I have SPSS output for a logistic regression model. The output reports two measures for the model fit, Cox & Snell and Nagelkerke. So as a rule of thumb, which of these $R^²$ measures would you report as the model fit? Or, which of these fit indices…
Henrik
  • 14,198
  • 11
  • 69
  • 130
1 2 3
…
99 100