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

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0
votes
1answer
25 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 ...
0
votes
0answers
22 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 ...
2
votes
1answer
34 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 ...
32
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
47 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
82 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
53 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
16 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
456 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
383 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
29 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
38 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 ...
0
votes
0answers
10 views

Signal dimension in regression model

Estimating Unknown Sparsity in Compressed Sensing is a paper about sparse signal. I am just learning the concepts. In the first paragraph, it says that when the number of observation data samples $n$ ...
4
votes
1answer
530 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
33 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 ...
1
vote
1answer
44 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
38 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
37 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
92 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 ...
4
votes
0answers
53 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, ...
1
vote
1answer
52 views

What is the difference between sample and outcome? (plus events and observations)

I was sure that these are the same things but I do not get the difference reading about mass probability function Suppose that $X: S → A (A \subseteq R)$ is a discrete random variable defined on ...
2
votes
1answer
74 views

Discrete analog of CDF: “cumulative mass function”?

We call the integral of a probability density function (PDF) a cumulative distribution function (CDF). But what's the cumulative sum of a probability mass function (PMF) called? I've never heard the ...
-1
votes
1answer
29 views

Hypothesis Testing terminology [duplicate]

I am studying now Hypothesis Testing. I use for it book High-Yield Biostatistics, Epidemiology, and Public Health and videos of Brandon Foltz (recommending these ...
0
votes
0answers
43 views

What is this problem called in machine learning research?

Given 2 sets of entities from 2 different classes described by properties $f_1...f_n$, any 2 entities from the 2 different classes together have a score: ${\rm Score}(c_1e_1,c_2e_1) = y$. How ...
2
votes
0answers
37 views

Where did the words bias and variance come from? [closed]

I understand that a bias model is more relaxed while a model with a lot of variance is more flexible. but, where did these terms come from, and, why 'bias' and why 'variance'?
1
vote
1answer
48 views

What are the Mild Regularity Conditions in the context of GEEs?

I was reading the Wikipedia Article on Generalized Estimating Equations, where I came across the following sentence: Parameter estimates from the GEE are consistent even when the covariance ...
1
vote
2answers
39 views

What is the correct term for testing a classification method on different subsets of the same data

I am searching for the correct definition of a methodology I am using to test the robustness of different classification methods. I am creating different subsets of the full dataset by cutting away ...
3
votes
1answer
52 views

Is there a formal name for this data normalization formula?

I am using a generalized formula for normalizing one data range to another but am having difficulty finding its formal name, if it even exists (sorry if my notation is strange): $$ x_b = min_b + ...
4
votes
1answer
53 views

What does “Conditioning on the margins of ____” mean?

What does it mean to "condition on the margin of ____"? I lack statistical/mathematical training and phrases like these leave me bewildered and unsure where to look. In this post (Which are ...
0
votes
3answers
118 views

What is shallow architecture in machine learning?

What is a precise definition of shallow architecture in machine learning?
2
votes
0answers
22 views

What's the difference between autoencoders and deep autoencoders?

I have seen the term deep autoencoders in a couple of articles such as Krizhevsky, Alex, and Geoffrey E. Hinton. "Using very deep autoencoders for content-based image retrieval." ESANN. 2011. What's ...
1
vote
0answers
44 views

What does “model-based” mean for multivariate statistics?

What does "model-based" mean for multivariate statistics? E.g. mvabund– an R package for model-based analysis of multivariate abundance data. How is "non-model-based multivariate statistics" then? ...
2
votes
1answer
62 views

Why we need single class classification?

I have started learning classification in machine learning. I face two terminologies, one is "single class classification" and a the other is "binary class classification". I am confused about when ...
8
votes
1answer
259 views

Is there a name for bar charts that replace the bars with color coded objects?

I have been trying to find information on this type of chart and just keep getting unintended results. Is there a name or search term to find bar charts that replace the bars with color coded objects ...
4
votes
2answers
198 views

Are “random sample” and “iid random variable” synonyms?

I have been facing hard time understanding meaning of "random sample" as well as "iid random variable". I tried to find out the meaning from several sources, but just got more and more confused. I am ...
1
vote
0answers
33 views

How do you explain dimension-reduction with statistics?

With statistics: how would you explain the dimensionality reduction and dimensionality addition? Like the conversion of a color picture to gray space so that a color blind person could more easily ...
1
vote
1answer
36 views

Family vs. class of distributions - definitions

What is the difference between a class of distributions and a family of distributions? The class of (a,b,0) distributions is defined as: The Binomial, Poisson, Geometric and Negative Binomial meet ...
0
votes
0answers
35 views

Geometric view of perceptrons

I'm watching Hinton's "Neural Networks for Machine Learning" on Coursera. I'm on the part about the geometric view of perceptrons. I'm confused. And the the reason I'm confused as I don't know what he ...
0
votes
0answers
27 views

What does “ordinate” in “posterior ordinate” mean?

What does "ordinate" in "posterior ordinate" mean? For example, The starting point in this computation is a decomposition of the posterior ordinate into marginal and conditional ordinates followed ...
2
votes
1answer
30 views

Correct expression of confidence level

A very basic question: when noting the statistical significance of fitting some model, does one report that results are significant at the 95 percent confidence level, or at 0.05 significance?
5
votes
0answers
43 views

Thesaurus for statistics and machine learning terms

Does there exist any reference thesaurus for statistics and machine learning terms? I know that Wikipedia articles often contain synonyms, but I would like to have a mere thesaurus that I could go ...
-4
votes
1answer
198 views

What are key differences between homoscedasticity and homogeneity?

Homoscedasticity and homogeneity assumptions are popular and perhaps deal with ANOVA and regression. These assumptions create lot of confusion.
9
votes
4answers
817 views

Can anyone clarify the concept of a “sum of random variables”

In my probability class the terms "sums of random variables" is constantly used. However, I'm stuck on what exactly that means? Are we talking about the sum of a bunch of realizations from a random ...
0
votes
1answer
55 views

Population Projection, Forecast, Prediction

I am frequently reading some terminology But not understanding their difference . Those are : $\bullet$Difference between ...
0
votes
1answer
64 views

Bernoulli or Binary RBM

For the classical RBM: $P(\tilde{h}|\tilde{x})=\sigma\left(\tilde{b}+W\tilde{x}\right) a$ and $P(\tilde{x}|\tilde{h})=\sigma\left(\tilde{c}+W^{T}\tilde{h}\right)$ for for hidden layer $\tilde{h}$ ...
1
vote
1answer
82 views

Bayes in English

I am not a statistician or mathematician but am trying to learn. My question: In Bayes Theorem, $p(C|X)=p(X|C)p(C)/p(X)$, what are the English terms for $p(X|C)$ and $p(C)/p(X)$? In other words, is ...
17
votes
5answers
2k views

What does 'highly non linear' mean?

I often read about a function being 'highly non linear'. In my understanding, there is "linear" and "non-linear", so what is this 'highly' about? Is there a formal difference from non linear? How is ...
7
votes
1answer
378 views

What is the difference between multiple regression & mutivariate regression?

I have data on GDP growth as a dependent variable and growth in main production sectors of Pakistan such as mining, electricity, communication, manufacturing and electricity. I am supposed to run a ...
0
votes
1answer
53 views

Transformation of latitudes to include them a linear model

I have in a dataset a variable latitude that contains values such as 39° 37' 39" N and ...