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1500 questions
190
votes
5 answers
How exactly does one “control for other variables”?
Here is the article that motivated this question: Does impatience make us fat?
I liked this article, and it nicely demonstrates the concept of “controlling for other variables” (IQ, career, income, age, etc) in order to best isolate the true…
JackOfAll
- 2,597
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188
votes
9 answers
How to summarize data by group in R?
I have R data frame like this:
age group
1 23.0883 1
2 25.8344 1
3 29.4648 1
4 32.7858 2
5 33.6372 1
6 34.9350 1
7 35.2115 2
8 35.2115 2
9 35.2115 2
10 36.7803 1
...
I need to get…
Yuriy Petrovskiy
- 4,081
- 7
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- 30
188
votes
2 answers
How do I get the number of rows of a data.frame in R?
After reading a dataset:
dataset <- read.csv("forR.csv")
How can I get R to give me the number of cases it contains?
Also, will the returned value include of exclude cases omitted with na.omit(dataset)?
Tom Wright
- 2,161
- 2
- 15
- 14
187
votes
10 answers
Why the sudden fascination with tensors?
I've noticed lately that a lot of people are developing tensor equivalents of many methods (tensor factorization, tensor kernels, tensors for topic modeling, etc) I'm wondering, why is the world suddenly fascinated with tensors? Are there recent…
Y. S.
- 1,237
- 3
- 9
- 14
186
votes
8 answers
What intuitive explanation is there for the central limit theorem?
In several different contexts we invoke the central limit theorem to justify whatever statistical method we want to adopt (e.g., approximate the binomial distribution by a normal distribution). I understand the technical details as to why the…
user28
183
votes
2 answers
How to determine which distribution fits my data best?
I have a dataset and would like to figure out which distribution fits my data best.
I used the fitdistr() function to estimate the necessary parameters to describe the assumed distribution (i.e. Weibull, Cauchy, Normal). Using those parameters I…
tobibo
- 1,935
- 3
- 11
- 8
182
votes
4 answers
Why do we need sigma-algebras to define probability spaces?
We have a random experiment with different outcomes forming the sample space $\Omega,$ on which we look with interest at certain patterns, called events $\mathscr{F}.$ Sigma-algebras (or sigma-fields) are made up of events to which a probability…
Antoni Parellada
- 23,430
- 15
- 100
- 197
178
votes
78 answers
Statistics Jokes
Well, we've got favourite statistics quotes. What about statistics jokes?
Thylacoleo
- 4,829
- 5
- 24
- 32
178
votes
5 answers
Training on the full dataset after cross-validation?
TL:DR: Is it ever a good idea to train an ML model on all the data available before shipping it to production? Put another way, is it ever ok to train on all data available and not check if the model overfits, or get a final read of the expected…
Amelio Vazquez-Reina
- 17,546
- 26
- 74
- 110
177
votes
8 answers
What does 1x1 convolution mean in a neural network?
I am currently doing the Udacity Deep Learning Tutorial. In Lesson 3, they talk about a 1x1 convolution. This 1x1 convolution is used in Google Inception Module. I'm having trouble understanding what is a 1x1 convolution.
I have also seen this post…
jkschin
- 1,873
- 3
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- 6
176
votes
8 answers
What is the influence of C in SVMs with linear kernel?
I am currently using an SVM with a linear kernel to classify my data. There is
no error on the training set. I tried several values for the parameter $C$
($10^{-5}, \dots, 10^2$). This did not change the error on the test set.
Now I
wonder: is…
alfa
- 2,505
- 3
- 15
- 15
174
votes
6 answers
Can a probability distribution value exceeding 1 be OK?
On the Wikipedia page about naive Bayes classifiers, there is this line:
$p(\mathrm{height}|\mathrm{male}) = 1.5789$ (A probability distribution over 1 is OK. It is the area under the bell curve that is equal to 1.)
How can a value $>1$ be OK? I…
babelproofreader
- 4,544
- 4
- 22
- 35
173
votes
4 answers
Choice of K in K-fold cross-validation
I've been using the $K$-fold cross-validation a few times now to evaluate performance of some learning algorithms, but I've always been puzzled as to how I should choose the value of $K$.
I've often seen and used a value of $K = 10$, but this seems…
Charles Menguy
- 2,277
- 4
- 15
- 16
173
votes
3 answers
How does Keras 'Embedding' layer work?
Need to understand the working of 'Embedding' layer in Keras library. I execute the following code in Python
import numpy as np
from keras.models import Sequential
from keras.layers import Embedding
model = Sequential()
model.add(Embedding(5, 2,…
prashanth
- 3,747
- 4
- 21
- 33
172
votes
7 answers
What's the difference between variance and standard deviation?
I was wondering what the difference between the variance and the standard deviation is.
If you calculate the two values, it is clear that you get the standard deviation out of the variance, but what does that mean in terms of the distribution you…
Le Max
- 3,559
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- 26
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