Questions tagged [terminology]

Usage and meaning of specific technical words/concepts in statistics.

Filter by
Sorted by
Tagged with
2 votes
1 answer
114 views

What is the name of the functions in exponential dispersion family?

If an exponential family is given by: $g(y|\theta) = exp\{\theta^TT(y)-A(\theta)\}h(y)$ then the functions $h(y)$, $A(\theta)$ and $T(y)$ are defined by names: $T(y)$ is a sufficient statistic $A(\...
user avatar
  • 97
0 votes
0 answers
49 views

How call a behavior of variable that is explained by other variable?

I have one dependent variable (it is a binary response variable that I want to predict, let's say "t1"), and also two independent variables ("v1" and "v2"). They are both ...
user avatar
0 votes
0 answers
21 views

Two random sequences converging to one another

Consider two infinite sequences $X_1, X_2, \dots$ and $Y_1, Y_2, \dots$. Suppose that $$\lim_{n\rightarrow \infty} |F_{X_n}(z) - F_{Y_n}(z)| = 0 ~~~~~~~~~~(1)$$ for all $z$ at which both cdf's are ...
user avatar
  • 183
0 votes
0 answers
25 views

The proper name of just subtracting the mean?

https://en.wikipedia.org/wiki/Normalization_(statistics) Normalization is subtracting the mean then dividing by the standard deviation. What is the name of just subtracting the mean?
user avatar
2 votes
1 answer
33 views

"De-meaning" or "Differencing the mean of..." in mathematical term

In a standard regression literature, the following terms are used almost interchangeably and are used also loosely: "De-meaning the equation gives..." "Differencing the mean of the ...
user avatar
2 votes
1 answer
25 views

Terminology of "Regression forest", "Random forest", "Decision tree" and "Regresion tree"

I am confused about the terminology of "regression forest", "random forest regression", "random forest", "decision tree" and "regression tree". As far ...
user avatar
  • 109
0 votes
0 answers
53 views

What is a "constant, random Gaussian vector"?

The paper "Path Integration and Cognitive Mapping in a Continuous Attractor Neural Network Model" by Samsonovich and McNaughton (Journal of Neuroscience 1 August 1997, 17 (15) 5900-5920) ...
user avatar
2 votes
1 answer
46 views

Cross-correlation seems defined backwards

Suppose $f$ and $g$ are real. Why $$ C(\tau)=(f\star g)(\tau) = \int_{-\infty}^{\infty} f(t) g(t + \tau)dt \tag{1} $$ and not $$ C(\tau)=(f\star g)(\tau) = \int_{-\infty}^{\infty} f(t) g(t - \tau)dt\...
user avatar
1 vote
1 answer
50 views

Can the term 'hyperparameter' apply to non-ML modelling?

Commonly when modelling biological systems, some parameters may be from elsewhere or previous modelling fits, and are not being investigated in the current model. These seem to be equivalent to the ML ...
user avatar
  • 15
0 votes
0 answers
9 views

Terminology clarification "decoder" (as in encoder-decoder model)

In an encoder-decoder model such as the Transformer model, what parts make exactly the decoder? Specifically, for designing a software implementation, and I want to implement a ...
user avatar
  • 1,155
0 votes
0 answers
25 views

Terminology "above and beyond"

What do researchers mean when they say predictor X accounted for a significant amount of variance above and beyond predictor A?
user avatar
  • 1
0 votes
0 answers
12 views

The meaning of "ICC corrected by age and comorbidity is best described in detail"

I received feedback on a manuscript comparing the mortality of two populations. Both crude and adjusted mortality rates are compared. Adjusting was done for age and comorbidity score and it is clearly ...
user avatar
  • 1,533
4 votes
2 answers
147 views

Mistake in Casella & Berger on page 207?

Page 28: A note on notation: Random variables will always be denoted with uppercase letters and the realized values of the variable (or its range) will be denoted by the corresponding lowercase ...
user avatar
1 vote
0 answers
36 views

On the naming of two different median estimators

Assume that $X \sim \mathcal{E}(\lambda)$ is, for example, exponential with $\lambda > 0$. Given a data sample $X_1, \ldots, X_n$, assume that I want to estimate the median of $X$. Consider these ...
user avatar
  • 632
0 votes
0 answers
15 views

How to talk describe log-transformed values in manuscript text

I'm editing a manuscript that I'm a coauthor on, and we are dealing with essentially log-normal data, so all of our statistical analysis was done using log-transformed values. I'm just trying to find ...
user avatar
  • 101
0 votes
0 answers
11 views

Right term for "Leave-Multiple-Feature-Out" feature importance?

I am working on a ML problem incorporating four data streams, each producing multiple features. We would like to know if each of the data streams provides a significant addition to the model ...
user avatar
2 votes
1 answer
38 views

What is the name for this time series rank plot?

from:https://2020.stateofjs.com/en-US/technologies/front-end-frameworks/ What is the name of this type of chart? How can I create the same chart in python ?
user avatar
1 vote
1 answer
61 views

Who proposed the reflective correlation coefficient?

The Wikipedia page for the Pearson product-moment correlation coefficient has a section on variants of the idea. This includes the reflective correlation coefficient, which has had a citation needed ...
user avatar
  • 3,403
2 votes
0 answers
34 views

How to name train + validation set

Usually in machine learning pipelines, we use a train set, a validation set and a test set. Quite often, we first split the test set from the rest, and then we split the "rest" into train ...
user avatar
0 votes
0 answers
8 views

Different Time Series CVs?

I'm writing a synthetic control algorithm which uses rolling-origin cross validation. Upon reading my paper, others have suggested I use "forward cv" and another paper I read seems to refer ...
user avatar
0 votes
0 answers
11 views

A terminology related to within-subject/between-subject design

I want to ask the terminology for this method: "I have run a survey with many respondents. There was a pool of questions, and each respondent was asked 3 of the questions (chosen uniformly at ...
user avatar
0 votes
0 answers
32 views

the difference between error and bias [duplicate]

after tossing a coin and analyzing the results of it, I conclude that the coin is biased. why do I not call the coin 'erroneous'? "Random error corresponds to imprecision, and bias to inaccuracy&...
user avatar
  • 57
1 vote
1 answer
17 views

Statistical terminology: "hazard ratio" or "hazards ratio"

I have a question related to statistical terminology. More specifically, about the hazard ratio. When describing the ratio between two hazard rates, we use the term "hazard ratio". The term &...
user avatar
0 votes
1 answer
19 views

What is the term for data which do not include multiple variables needed for controlling confounding in analyses?

I have a terminology question that I couldn't answer by googling. What is the term for data which do not include multiple analytically relevant variables needed for controlling confounding in analyses?...
user avatar
  • 1,533
0 votes
1 answer
43 views

Root Mean Square value, but with reverse order of operation

I've got a question about name of some specific value. Root Mean Square value is defined as such: $$ RMS = \sqrt{\frac{1}{N}\sum_{i}^{N}{x_i^2}} $$ I came across a value, that is similar, but is ...
user avatar
0 votes
0 answers
21 views

What is the Complement of Discriminant Analysis?

When Discriminant analysis is concerned with the relationship between a categorical variable and a set of interrelated variables. [1] And [...] in discriminant analysis the existence of groups is ...
user avatar
0 votes
1 answer
29 views

Synonyms of Residual Sum of Squares

As a novice, I'm finding it difficult to learn statistics, partly because there are often many different words for the same thing. When I'm reading about stats, I don't realize that the thing I'm ...
user avatar
2 votes
1 answer
30 views

What is the proper name for the *other* type of "conditional entropy"?

Suppose we have two random variables $X$ and $Y$ (for simplicity of exposition I will take these to be discrete). If we were to condition our entire analysis on the event $X=x$ and then ask for the ...
user avatar
  • 94.4k
0 votes
0 answers
20 views

What is the difference between a hypothesis and a target function?

What exactly is the difference between a hypothesis and a target function? According to my understanding, the hypothesis determines the target value for each instance, and the target function also ...
user avatar
2 votes
1 answer
130 views

Can the sample equal the population?

I came across this test question from an introductory statistics course for undergraduates in biology. The solutions are in square brackets. Which cases are possible? The sample is larger than the ...
user avatar
1 vote
2 answers
61 views

Is there a term for this concept (Randomly Random)?

Let's say I have what appears to be a fair dice that over 10K fair throws it produces very close to 1/6 occurrences of each face value. But then one day it starts a string of throws where the 3 face ...
user avatar
0 votes
1 answer
120 views

Is there a difference between perfect collinearity and multicollinearity?

I've read that for multiple regression analysis there is an assumption of no perfect collinearity. Is that the same as multicollinearity?
user avatar
0 votes
0 answers
14 views

How to unambiguously communicate that a trend line through data is not presumed to be predictive?

I placed a regression line through data purely as a visual aid: The problem is there is a non-trivial risk that someone (especially non-statisticians) may interpret this regression line through the ...
user avatar
  • 259
0 votes
0 answers
56 views

Can we call "Regularization" as "Constrained Optimization"?

I have the following question on "Regularization vs. Constrained Optimization" : In the context of statistical modelling, we are often taught about "Regularization" as a method of ...
user avatar
  • 5,750
4 votes
0 answers
33 views

The use of a pseudo variance $\int_{-\infty}^\infty \text{sign}(x) (x-\mu)^2 f(x) dx$ in place of $\int_{-\infty}^\infty (x-\mu)^2 f(x) dx$

Difference between odd central moments and even central moments When we compute $n$-th central moments $$\mu_n = \int_{-\infty}^\infty (x-\mu)^nf(x) dx$$ then there is a difference in interpretation ...
user avatar
0 votes
0 answers
12 views

What is the correct terminology of x→y in moderation/interaction effect analyses?

Writing my first article within moderation analyses, I would like to know if it is ok to call the x->y (and z->y) effect a "direct effect" or if I should just call it an "effect&...
user avatar
0 votes
0 answers
27 views

What's the property of a metric that defines if an increasing value is good or bad called?

For instance, an increasing trend for a revenue metric is good, while bad for something like the number of defects per million. What is the correct technical term to describe this property of a metric....
user avatar
2 votes
0 answers
35 views

What do you call it when you regress a dependent variable's variance on some predictors?

What do you call it when you regress a dependent variable's conditional variance , not its conditional mean, on a set of predictors? In the "simple" case, I suppose you could figure that ...
user avatar
  • 18.6k
3 votes
1 answer
150 views

Can we talk about statistical significance using Bayesian Inference?

In short: can we use the words statistical significance when interpreting the hypothesis testing results in the bayesian inference field ? Or is it only correct to use it in the frequentist approach ? ...
user avatar
  • 31
1 vote
1 answer
58 views

Difference between residuals and idiosyncratic errors?

I have a simple question. I want to know the difference between the residuals obtained from a model and idiosyncratic errors.
user avatar
  • 109
3 votes
0 answers
58 views

Using the terminology "Bayesian confidence interval" in place of "Bayesian credible interval."

In Peter Hoff's "A first course in Bayesian statistical methods," he states: "Most authors refer to intervals of high probability as 'credible intervals' as opposed to confidence ...
user avatar
  • 43
0 votes
0 answers
25 views

What is the name of the data set used to calibrate FPR and FNR for a model?

In spam classification domain, we often train the models on different sets than the production. Then we are faced with the problem of calibrating the models with ROC curves to find a proper cut-off ...
user avatar
1 vote
1 answer
93 views

Can "Prediction" and "Inference" be used Interchangeably? [duplicate]

Within statistics, I have heard that almost all analysis can be broken into two general classes: Prediction : E.g. Statistical Modelling, Machine Learning Inference I have seen the term "...
user avatar
  • 5,750
4 votes
2 answers
676 views

Is correlation a percentage?

The Pearson correlation coefficient ranges from -1 to 1. Oftentimes, people take this number, multiply it by 100 and call it -17.3% correlation or 63% correlation I was once dinged by reviewers ...
user avatar
  • 1,173
4 votes
1 answer
142 views

Name of the formula which links the expectation of a random variable with the summation of the product between conditioned expectation and probability

I'd like to know the English name of the following property of the expectation ($X$ random variable; $(A_i)_{i=1}^n$ partition of a set): \begin{equation} \mathbb{E}[X] = \sum \limits _{i = 1}^{n} \...
user avatar
0 votes
0 answers
15 views

Difference Between "General" and "Canonical" in Statistics

I often hear the words "general" and "canonical" used in statistics - for example, "generalized linear models" and "canonical solutions". For example, I have ...
user avatar
  • 5,750
2 votes
1 answer
46 views

Can a sampling distribution have only 1 element or is it necessary to have multiple data elements to be a sampling distribution? [closed]

Can we have a sampling distribution of only 1 realization or is it necessary to have multiple data elements to be a sampling distribution?
user avatar
  • 21
4 votes
2 answers
99 views

What is a formal definition of the unique values in an array?

Let the term unique be defined as all other values of this object are numerically different from one value of this object. Let $v$ be a vector with 5000 observations with each observation may or may ...
user avatar
  • 218
0 votes
0 answers
15 views

Are weighting in deep learning and using weighted loss refer to the same thing?

I was searching about what exactly means applying a weighted loss function in deep learning. While searching on that I also came across the weighting in deep learning. Do they refer to the same ...
user avatar
  • 189
0 votes
1 answer
43 views

Type of regression

I have a regression model that looks like this: $$y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \beta_3 X_1 X_2 + \beta_4 X_1X_2$$ What is the correct name for this regression: multiple linear regression? ...
user avatar

1
2 3 4 5
31