Indicates questions asking about the use and meaning of specific technical words/concepts in statistics.

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3
votes
1answer
62 views

Applied statistics vs Mathematical statistics [closed]

The Help Center for this site says we can ask question about, among other things, mathematical statistics. I am curious to find out what mathematical statistics is. And I thought it might be easier ...
6
votes
2answers
95 views

Is 'indirect effect' the same as 'mediation'?

Is it correct to use 'indirect effect' and 'mediation' interchangeably in all situations? I mean if we know that A influences B and B influences C. Can we conclude that the effect is mediated by B ...
5
votes
1answer
70 views

Why do we use the term multicollinearity, when the vectors representing two variables are never truly collinear?

When two vectors $a$ and $b$ are collinear, then $a = xb$, (where $x$ is a scalar) so in linear algebra, collinearity is a narrowly and clearly defined (and binary) concept. Two vectors -- in my ...
6
votes
1answer
355 views

What is cross-validation?

I'm having trouble understanding what cross-validation is. Also, what is the connection between cross-validation and the issue of model overfitting?
3
votes
1answer
46 views

Bayesian linear regression with continuous and binary covariates

I am interested in learning more about applying Bayesian linear models for covariates some of which are continuous and some are binary. What is the appropriate terminology for such models so that I ...
7
votes
2answers
93 views

How to describe a bin in a histogram?

What is common in the literature to refer to a certain bin in a histogram? For example, say I have a histogram with 4 bins. The first bin has all values between 1 to 2, second bin 2 to 3, and so on. ...
4
votes
1answer
29 views

What does the SEE measure?

Depending on context, I've seen the term "Standard Error of Estimate" used for both the standard deviation and for the variance of both the standard error and of the residuals. Is SEE a well-defined ...
8
votes
1answer
287 views

How does “Fundamental Theorem of Factor Analysis” apply to PCA, or how are PCA loadings defined?

I'm currently going through a slide set I have for "factor analysis" (PCA as far as I can tell). In it, the "fundamental theorem of factor analysis" is derived which claims that the correlation ...
4
votes
1answer
113 views

“Dummy variable” versus “indicator variable” for nominal/categorical data

"Dummy variable" and "indicator variable" are labels frequently used terms to describe membership in a category with 0/1 coding; usually 0: Not a member of category, 1: Member of category. On ...
1
vote
1answer
57 views

What is the difference between a distribution and a semi-distribution?

I hope the question to be clear. The name "semi-distribution" certainly implies some meaning, yet, I'm unable to conclude what really means. I found the term on this paper: ...
10
votes
2answers
572 views

How to understand “nonlinear” as in “nonlinear dimensionality reduction”?

I am trying to understand the differences between the linear dimensionality reduction methods (e.g., PCA) and the nonlinear ones (e.g., Isomap). I cannot quite understand what the (non)linearity ...
4
votes
1answer
60 views

impose an intercept on lm in r [duplicate]

I am converting a high-dimensional model to a lower dimensional model by fitting a sliding window of it to a linear (parametric) model and looking at the evolution of parameter values over time. I'm ...
0
votes
0answers
26 views

Confidence interval violating physical boundaries

Colleagues, A model is supposed to predict a value that represents proportion, namely, the predicted value should be in [0,1]. However, model is just a linear regression, producing confidence ...
2
votes
0answers
22 views

How to call “Inliers” and “Outliers” in French

I asked this on the French Exchange site, but this is stat related so... How do you say "Inliers" and "Outliers" (as with RANSAC) in French? The Wikipedia article doesn't translate them, but honestly ...
0
votes
1answer
35 views

Are “Probability Distribution” and “Probability Function” the same thing?

I have these two definitions for "Probability distribution" and "Probability function": Probability Distribution: Assigns a probability to each measurable subset of the possible outcomes of a ...
0
votes
1answer
64 views

Interpreting rpart output for decision trees?

How do I go about selecting the ideal location to use for pruning the tree here? Or maybe someone can explain to me in simple language what this output means. I see that rel_error is constantly ...
4
votes
3answers
212 views

What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall?

Despite having seen these terms 502847894789 times, I cannot for the life of me remember the difference between sensitivity, specificity, precision, accuracy, and recall. They're pretty simple ...
3
votes
2answers
61 views

Name for outer product of gradient approximation of Hessian

Is there a name for approximating the Hessian as the outer product of the gradient with itself? If one is approximating the Hessian of the log-loss, then the outer product of the gradient with itself ...
0
votes
2answers
44 views

Use of the term “outcome”

I know that a particular value a variable can have is called an outcome. Sometimes I see that a dependent variable is also called an outcome. Is the latter use a legitimate practice or bad use of the ...
0
votes
0answers
28 views

Ways to express the relationship between a latent variable and observables

How do I express concisely the idea that the values of a number of observables is determined stochastically by the value of a latent variable? Can I say: The value of the latent variable is ...
0
votes
0answers
20 views

Cannot intuitively grasp “Standard normal deviate”

I cannot intuitively grasp the meaning of "Standard normal deviates". I think It would help if you provided me with either/all of the following: (i) real life examples of their application, (ii) an ...
8
votes
5answers
279 views

What exactly are censored data?

I have read different descriptions of censored data: A) As explained in this thread answer, unquantified data below or above a certain threshold is censored. Unquantified means data is above or below ...
2
votes
1answer
113 views

What is the difference between logistic and logit regression?

What is the difference between logistic and logit regression? I understand that they are similar (or even the same thing) but could someone explain the difference(s) between these two? Is one about ...
3
votes
2answers
134 views

What makes a GLM Hierarchical?

Wikipedia defines a Hierarchical GLM as: Hierarchical linear models (or multilevel regression) organizes the data into a hierarchy of regressions, for example where A is regressed on B, and B ...
1
vote
0answers
43 views

Conditional independence: conditioning on an empty set of random variables

Is $X \perp\!\!\!\perp Y$ a conditional independence, arguing that the independence is conditioned on an empty set of random variables? If so, does that mean that an unconditional independence is ...
0
votes
1answer
24 views

Factor graph vs Factor graphical model

In inference we use the terms undirected graphical models and directed graphical models. Why do we say factor graph instead of factor graphical models?
4
votes
1answer
172 views

Unusual Terminology in Hartigan's DIP paper?

In Hartigan's DIP test paper, it says A distribution function $F$ is unimodal with mode $m$ if $F$ is convex in $(-\infty,m]$ and concave in $[m,\infty)$. Shouldn't that be a cumulative ...
2
votes
1answer
30 views

What is $I(X_i < \overline{X})$?

I have a problem that involves the term $I(X_i < \overline{X})$. The only reference to this in the question is "trimmed means", but I believe it references the entire function $\frac{\sum X_i I(X_i ...
0
votes
1answer
36 views

Nomenclature: What is the proper term to describe the probability of event A divided by the probability of event B?

I have a hidden markov model that scores the probability of various state sequences (paths). For simplicity, I will talk about a state sequence as an event. I am calculating how much more probable one ...
4
votes
2answers
119 views

Many dependent variables, few samples: is this an example of “large $p$, small $n$” problem?

"Large $p$, small $n$" typically refers to "many independent variables, few samples". In my case, I have $1$ independent variable, $300$ dependent variables, and $n < 20$ samples. Thus, my case ...
0
votes
0answers
29 views

Is this a case of semi-supervised classification?

I have a rule-based classifier and I know for sure I can classify my data in a number of N classes. And I have also a "small" dictionary where my rules check (during classification process) for every ...
3
votes
1answer
37 views

Is the distribution of the minimum of two other distributions a mixture distribution? Or is there a better term?

This is a terminology question motivated by a review that I got on a paper. In the following I believe that $y$ would be considered to be distributed according to a mixture distribution: $$y \sim ...
33
votes
9answers
4k views

When teaching statistics, use “normal” or “Gaussian”?

I use mostly "Gaussian distribution" in my book, but someone just suggested I switch to "normal distribution". Any consensus on which term to use for beginners? Of course the two terms are synonyms, ...
0
votes
1answer
51 views

Which is a statistic, $T(X)$ or $T$?

This is a terminology question. Is $T(X)$ or $T$ a statistic? $X$ is a random variable, and $T$ is a measurable mapping. I ask this because, I want to know how to say the distribution of $T(X)$ ...
4
votes
1answer
92 views

Are Auto-Associative Regression Trees Distinct from Auto-Regressive Trees?

After some reading in the field I was confused as to whether these two models are distinct or really the same. I'm just looking for a simple yes/no with a brief explanation. Note that ...
4
votes
1answer
58 views

Prediction vs. Explanation and its Effect on Statistical Methods [duplicate]

In layman's terms, what is the difference between predicting and explaining in statistics? I was looking for the differences between AIC and BIC and found this post with an answer stating: My ...
1
vote
1answer
21 views

Why is it called Epsilon for DBSCAN?

The two parameters of DBSCAN are epsilon and minimum samples. Shouldn't epsilon be called like "Circle radius"? Why is it called epsilon?
8
votes
2answers
466 views

What is meant by the term 'exponential family'? Why it is named so?

I have come across the term exponential family. The Bernoulli, Gaussian and many more distributions come under this exponential family. What would be the commonalities between them?
7
votes
3answers
493 views

What does “curvilinear” mean?

As far as I can tell, curvilinear is defined vaguely but means the same as nonlinear. Is that correct? Or does curvilinear have a distinct definition?
0
votes
1answer
50 views

Linear Factor Model vs. Linear Regression Model

I've been reading some literature that discusses 'linear factor models' which appear to describe the general equation often used in OLS regression. When people refer to a 'linear regression model' ...
3
votes
2answers
40 views

Terminology for how “grouped” an ordered data set is

Apologies in advance for poor terminology / description below; I'm trying my best but I do not know the correct wording. Let's say a "sample" is some fixed number $n$ of boolean values (I'll use ...
4
votes
1answer
542 views

What is being learnt?

This may seem a trivial question but I have a fundamental problem in understanding learning. In supervised learning, given and input-output pair, what are we learning? Are we learning the inputs ...
0
votes
1answer
152 views

What is linear separability of classes and how to determine

This question may seem too trivial but my basics are not strong and I shall appreciate help in these concepts. For an n dimensional feature vector and 3 class problem does linear separability need to ...
0
votes
1answer
51 views

Difference between estimation and learning

What is the difference between parameter estimation which includes system identification and learning in machine learning perspective? Let say the model is y= Ax. x is the input and y is the output. ...
0
votes
1answer
66 views

How to normalize time series?

This is a general question on normalization of data so that all the variables are within the same range. Why do we normalize data in pattern classification? How to normalize time series which is ...
1
vote
1answer
49 views

Confusion regarding correlation and correlation coefficient

Can somebody provide an intuitive difference between correlation and correlation coefficient? During learning of weights of neural network, I want to show how closely the estimated weights are to the ...
1
vote
1answer
285 views

What is the difference between ex ante and a priori, if any?

In the context of estimating geophysical quantities from remotely sensed data (inverse theory), what do the terms ex ante and ex post mean? For context, see for example this paper by T. von Clarmann ...
2
votes
0answers
35 views

What is a semantic map

Based on: J. P. Carvalho, "On the Semantics and the Use of Fuzzy Cognitive Maps in Social Sciences" (WCCI, 2010 -- PDF) and Richard Dagan's web page Cognitive Mapping. A cognitive map consists of ...
5
votes
0answers
60 views

Weighting on tables

I have a question about terminology. Suppose I have data categorized by three factors A, B, and C, with cell means $\bar{y}_{ijk}$ and cell frequencies $n_{ijk}$, where $i$, $j$, and $k$ index A, B, ...