Top new questions this week:
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Deep learning methods are often said to be very data-inefficient, requiring 100-1000 examples per class, where a human needs 1-2 to reach comparable classification accuracy.
However, modern datasets ...
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In Bayesian statistics, parameters are said to be random variables while data are said to be nonrandom. Yet if we look at the Bayesian updating formula
$$
p(\theta|y)=\frac{p(\theta)p(y|\theta)}{p(y)},...
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Let's say I have a dataset to which I have estimated a relationship using non-parametric regression, specifically Kernel (obviously in this hypothetical example it's probably overfit slightly). The ...
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In parameter estimation, it's common to report a 95% CI around each parameter. Why don't I see AIC (or deltaAIC) with a CI?
If I bootstrap the fitting of two potential models, and get a deltaAIC for ...
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For maximum likelihood estimation we need to set the first derivative of the log-likelihood function equal to $\mathbf{0}$.
The negative expected value of the Hessian matrix (second derivative) is ...
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I'm going through the Dragonnet paper (slides available here), and the authors use Pearl's do notation to make this claim:
How can I interpret the do notation? Is the author claiming that the average ...
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The formula to calculate standard error (aka standard deviation of the sample mean) is $\sigma_{\bar{x}} = \frac{ \sigma} {\sqrt{n}}$. But we generally don't know the population standard deviation $\...
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Greatest hits from previous weeks:
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Two terms normal distribution and standard normal distribution are used in statistics. Does standard term contribute to the normal distribution anything? Please give a simple-however a substantive ...
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I want to know how to check a data set for normality in Excel, just to verify that the requirements for using a t-test are being met.
For the right tail, is it appropriate to just calculate a mean ...
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I am working with a small dataset (21 observations) and have the following normal QQ plot in R:
Seeing that the plot does not support normality, what could I infer about the underlying distribution? ...
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They seem so similar. Are they the same thing but just referred to as different names?
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I am trying to understand how, using only the standard deviation and mean, you are able to determine the first and third quartiles on a normal distribution.
I get that the area under the curve equals ...
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What is the difference between a population and a sample? What common variables and statistics are used for each one, and how do those relate to each other?
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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 ...
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Can you answer these questions?
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If I have two sets of data, find the probability that one set of data will have a higher value
i.e. for sets A and B:
if you took one random variable from each set, one is more likely to be greater
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Suppose we have three categories with $p_1+p_2+p_3=1$. And suppose we have already derived these two (say 95%) symmetric confidence intervals: $$
p_1 \in\ (L_1, U_1),\quad p_1 + p_2 \in\ (L_2,U_2).
$$
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For simplicity, consider a Generalized linear model (GLM) for the losses reported to an insurance company for damage to a building. A standard GLM assumes the randomness of the outcomes to be ...
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