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Applied and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments.

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name for $\underset{x}{\operatorname{argmin}} \displaystyle\sum\limits_{i=1}^n |x_i - x|$

The value of $x$ that satisfies this is the median of $x_i$. It minimizes $L_1$ loss. Note that the mean of $x_i$ is the value of $x$ minimizing $\sum(x_i - x)^2$, the $L_2$ loss.
David Harris's user avatar
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1 vote
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Role of statistical estimation in formal proof

Consider the following scenario: There is some mathematical constant $c$ that you want to compute. You don't have a formal proof for any particular value of $c$, but you have some sound statistical pr …
David Harris's user avatar
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1 vote

Question on Maximum Likelihood Estimation

You definitely would run into identification issues. Suppose $f(x|\mid\theta) = x \theta$. Then multiplying $\theta$ and $\sigma$ by any common factor would result in an identical situation. In this …
David Harris's user avatar
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1 vote
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Standard Deviation of Averages of Random Numbers

Let $Y$ the be mean of $t$ samples of the distribution. $Y$ has mean $1/2$ and variance $1/(12 t)$. Then $f_s(t)$ is the sample standard deviation of $s$ draws from $Y$. As the sample standard deviati …
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1 vote

Statistics - Subpopulation Random Sampling

This is not correct. We do not know that 70% of population A is male and 70% of population B is male. It may be that the populations are correlated. For example, if A = population has beards, B = popu …
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How many samples to be confident?

If you have probability distributions $p_0, p_1$, then the proper statistic is the bayes factor $p_0(\vec x)/p_1(\vec x)$ where $\vec x$ is the vector of observations. This yields the most powerful te …
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