This tag indicates questions about definitions of statistical terms. Use a more general tag [terminology] for questions on statistical parlance that are not specifically about definitions.

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3
votes
1answer
19 views

Conditioning within definition explanation

I have a doubt on the meaning of a conditioning within a definition. In a book I've found the following definition of upper tolerance limit: $P(P(X<\bar X+kS|\bar X, S)>p)=1-\alpha$ where $X$ ...
1
vote
0answers
25 views

Notion of “the same” distribution in definitions of “iid” and “exchangable”

Schervish's (1995) Theory of Statistics defines exchangeability like this (p. 7): A finite set $X_1, …, X_n$ of random quantities is said to be exchangeable if every permutation of $(X_1, …, X_n)$ ...
1
vote
0answers
15 views

Time series with slightly unequal intervals

I'm very new to statistics, and I have a problem that may or may not exactly be considered a time series analysis problem. I have a large set of vehicle location measurements (x0, y0)...(xt, yt) taken ...
0
votes
1answer
46 views

Difference between random walk and martingale

I am trying to understand the diffrence between random walk and martingale. According to my understanding, a random walk without drift is $$ y_{t} = y_{t-1} + u_{t} $$ where $u_{t}$ is $i.i.d.(0, \...
3
votes
0answers
38 views

Definition of “meta-parameter” [duplicate]

What is meant by the term "meta-parameter"? Can a definition, informal and/or formal, be provided? For example, in reduced-rank regression, the rank ($r$) can be referred to as a meta-parameter of ...
7
votes
1answer
404 views

What is skewness of a distribution?

What is skewness of a distribution? I ask it why any particular indices seem indecisive about symmetry, and in some case also about asymmetry.
2
votes
1answer
33 views

Definition of Stable convergence in law: why do we need an extension of the probability space?

I am trying to understand the definition of stable convergence in law. I have found the following definition. Definition. Let $Y_n$be a sequence of random variables defined on a probability space $(\...
4
votes
2answers
168 views

Does “improper” posterior or prior refer to a density function that does not integrate to 1 or to one that does not integrate to a finite value?

I am a bit confused about improper priors and posteriors. I have seen references that classify a prior or posterior probability density function as "improper" if the integral over infinite support ...
4
votes
1answer
130 views

do(x) operator meaning?

I have seen the $do(x)$ operator everywhere in some literature review I am doing on Causality (see, for instance this wikipedia entry). However, I cannot find a formal and general definition of this ...
10
votes
3answers
557 views

Is there a formula for computing median?

Is there an equivalent of the mean formula: \begin{equation} \mathrm{mean} = \cfrac{1}{N} \sum_{i=1}^{N} X_i \end{equation} for median?
15
votes
5answers
812 views

What's in a name: hyperparameters

So in a normal distribution, we have two parameters: mean $\mu$ and variance $\sigma^2$. In the book Pattern Recognition and Machine Learning, there suddenly appears a hyperparameter $\lambda$ in the ...
2
votes
2answers
133 views

What is an isotropic (spherical) covariance matrix?

Could somebody explain to me in simple terms what an isotropic covariance matrix is? I can't find anything online.
0
votes
0answers
23 views

Difference between Discrimination, Calibration, Accuracy and Precision

I have trouble understanding these terms: a.) Discrimination. b.) Calibration. c.) Accuracy. d.) Precision. I really get confused with the books I am reading, ...
5
votes
1answer
79 views

Do we say that the $y_i$'s are i.i.d. if $n_iy_i \sim \text{Binomial}(n_i, \theta)$?

If $y_i$'s are independent and for given $n_i$, $$n_iy_i \sim \text{Binomial}(n_i, \theta)$$ Could we say that $y_i$'s are i.i.d.? If not, then what's the proper way to address such problems?
0
votes
0answers
17 views

What are dynamical process?

Can someone explain to me what are Dynamical processes? It would be helpful if someone can also give me an example/s (if possible, in context of atmospheric or environmental processes) regarding this.
0
votes
0answers
33 views

Layman's definition of high-dimensional data

I'm a statistician writing a research proposal to be read by non-statisticians. This will mostly include mathematicians, computer scientists, and engineers, but may also include those in humanities. ...
130
votes
11answers
12k views

What is a data scientist?

Having recently graduated from my PhD program in statistics, I had for the last couple of months began searching for work in the field of statistics. Almost every company I considered had a job ...
0
votes
1answer
16 views

remove the mean over multiple measurements

I have a set of multiple measurements for each subject (i.e. each subject is assessed several days). For each set of measurements (several days of the same subject) I am calculating the mean value of ...
0
votes
1answer
28 views

Ground truth Vs. Baseline [closed]

I was wondering what the difference between ground truth and baseline is? Is it necessary that a system should always be tested ...
1
vote
0answers
14 views

Equivalence of definitions of quantiles

Let us define the concept of quantile of order $\tau$ of a random variable $X\in F$ in two different ways: Definition $1$: $c_\tau$ is said to be a quantile of order $\tau$ if and only if $lim_{x\to ...
2
votes
1answer
67 views

What makes something a “Probability”?

What makes it legitimate to say a set of values are probabilities? (I need an answer for a formalisation reasons.) Let me give a simple example. Let's assume that I have a number of letters and each ...
1
vote
0answers
15 views

Well defineness of the definition of F1 score

The F1 score is defined as the harmonic mean of precision and recall: $$ F_{1}=2\cdot {\frac {\mathrm {precision} \cdot \mathrm {recall} }{\mathrm {precision} +\mathrm {recall} }}.$$ The above ...
0
votes
1answer
61 views

What is $p_i(x_i - \sum_i p_ix_i)$ called?

I was reading a paper (dont have it with me!) on statistics and found a term that I have never encountered before: $p_{i}{(x_{i}-\mu )} = p_i(x_i - \sum_i p_ix_i)$ After some research it seems that ...
11
votes
2answers
346 views

Mathematical definition of Infill Asymptotics

I am writing a paper that uses infill asymptotics and one of my reviewers has asked me to please provide a rigorous mathematical definition of what infill asymptotics is (i.e., with math symbols and ...
0
votes
0answers
108 views

What is a grade-tonnage curve?

What is a grade-tonnage curve ? I cannot find any good online resource, neither wiki, neither any forum... Thanks, PS: sorry if it should be on another website
3
votes
3answers
54 views

Limiting the range of numbers

Suppose that I have the following data set: {0.1, 0.2, 0.5, -0.1, 0.5, 1.1, 0.8} I would like to limit the range of these data to be within the range of [0,1]. ...
2
votes
1answer
33 views

On the definition of covariance matrix

I am having a misunderstanding with the definition of the covariance matrix from the wikipedia page on the covariance matrix. It says the covariance matrix $\sum$ is equivalent to where It ...
1
vote
0answers
32 views

What does error mean in this context?

In the paper: Avrim L. Blum and Pat Langley. 1997. Selection of relevant features and examples in machine learning. Artif. Intell. 97, 1-2 (December 1997), 245-271. are several definitions of the ...
1
vote
1answer
61 views

Defintion of the terms “node weight” and “case weight”

In the literature about decision tress and especially the family of tree approaches that avoid selection bias (conditional inference trees e.g. here: ctree: Conditional Inference Trees by Hothorn, ...
7
votes
1answer
553 views

What is the mathematical definition of location / scale / shape parameters?

I am trying to understand the exact definition of the location / scale / shape parameters (e.g. $a$ is called the shape parameter and $c$ is scale parameter in Pareto Type I). But the books I referred ...
2
votes
1answer
119 views

Confusion about concept of likelihood vs. probability

I've been recently trying to wrap my head around the concept of likelihood, and have made some good progress, but there is one thing that is bugging me, and I think this issue is what makes the ...
3
votes
2answers
68 views

Is $P(X_t=Y_t,\forall\ 0\leq t < \infty )$ well defined?

I have an elementary question about stochastic processes (continuous) and the notion of two processes being indistinguishable. Let $X=(X_t)_{t\geq 0}, Y=(Y_t)_{t\geq 0}$ be two stochastic processes on ...
4
votes
3answers
120 views

Definition and delimitation of regression model

An embarrassingly simple question -- but it seems it has not been asked on Cross Validated before: What is the definition of a regression model? Also a support question, What is not a ...
3
votes
1answer
61 views

Is a random variable taking every rational number or a range of rational numbers discrete or continuous?

My guess would be discrete because such a variable would only take a countable set of values and "continuous" seems to imply the continuum of the real numbers.
2
votes
1answer
73 views

Am I understanding differences between Bayesian and frequentist inference correctly?

Given a sequence of independent experiments, each having as its outcome either success or failure, the probability of success being some number p between 0 and 1: A Bayesian would consider the ...
2
votes
2answers
173 views

How exactly do Bayesians define (or interpret?) probability?

Part of a series of trying to understand Bayesian vs frequentist: 1 2 3 4 5 6 7 I think I get the difference of how Bayesians and frequentists approach choosing between hypotheses, but I'm not quite ...
1
vote
0answers
69 views

What is the difference between a flat and weak prior?

Flat and weak prior distributions are two possible types of prior in Bayesian statistics. In layman's terms, what are the key differences between the two, and why do we use one or the other? ...
1
vote
1answer
68 views

What does 'downward pressure on sample size' mean?

In this article, there is this phrase 'downward pressure on sample size'. This is the paragraph: no matter the approach to collecting this new data, when attempting to ...
1
vote
1answer
45 views

Correlation matrix for uncorrelated parameter esitmates

I have a set of $n$ parameter estimates. How can I understand if they are correlated or uncorrelated? I guess I should calculate the correlation matrix. How is it exactly defined in terms of the ...
0
votes
0answers
49 views

What's a linear aggregate?

A paper I'm reading (Davis-Stober et al, 2014) contains the following statement: A crowd is wise if a linear aggregate, for example a mean, of its members’ judgments is closer to the target ...
1
vote
1answer
332 views

Difference between within-group and between-group covariance matrices in linear discriminant analysis

Could someone explain to me the difference between within-group covariance matrix and between-group covariance matrix in the context of linear discriminant analysis?
2
votes
1answer
219 views

What is the definition of “rare events”? and when it matters for significance testing of differences in a control-case study?

What is the formal definition of "rare events"? and when it matters for significance testing of differences in a control-case study?
2
votes
3answers
655 views

Ground-truth definition

I have found two meanings of how "ground truth" is being used in machine learning: Something to be assumed true Something previously validated as true Although similar in detail the two can differ....
1
vote
1answer
89 views

Computing required sample size for paired t-test

I have some paired t-test data (40 pairs) and I would like to use these data to estimate the sample size required if I were to conduct the study again with a new set of requirements. I'm using ...
0
votes
1answer
31 views

Obvious counter examle to the Handshaking Lemma [closed]

The Handshaking Lemma is described thusly in Wikipedia: In graph theory, a branch of mathematics, the handshaking lemma is the statement that every finite undirected graph has an even number of ...
2
votes
1answer
251 views

Is there a difference between on-line learning, incremental learning and sequential learning?

What I mean is the following: Instead of processing all the training data at once and calculating a model or hypothesis, we process one data point at a time and update the model directly afterwards. ...
0
votes
0answers
35 views

What, if any, is the precise definition of “substantively large”?

I am told that while my estimates are not statistically significant, they are "substantively large". Is there a precise definition for the phrase "substantively large"? If I say that my estimates (...
0
votes
0answers
109 views

Homoscedasticity - constant second moment or constant variance

I found the following different definitions of homoscedasticity and I'm wondering which is the correct one. The second moment is constant, i.e. E(X²)=s² (see e.g. p.11 http://press.princeton.edu/...
9
votes
1answer
587 views

What do we mean by hyperparameters? [duplicate]

Can anyone give me full details about what we mean by hyperparameters, and what in the Dirichlet distribution are called hyperparameters? A practice example for the estimation of those parameters ...
2
votes
1answer
39 views

Reference for definition of multiple-output Gaussian process

Does anyone know any good reference that has a clear and precise definition of multiple-output Gaussian process? Something like the definition of the Gaussian process in the third page of this set of ...