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

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0answers
16 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
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1answer
94 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
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2answers
111 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 ...
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0answers
17 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 ...
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1answer
19 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
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1answer
159 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
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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 ...
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1answer
33 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 ...
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0answers
24 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
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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
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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
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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
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1answer
87 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
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1answer
54 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
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1answer
17 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
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2answers
459 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
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3answers
396 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
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1answer
30 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
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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 ...
5
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1answer
532 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
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1answer
47 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 ...
2
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1answer
47 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
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1answer
40 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
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1answer
42 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
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1answer
122 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
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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
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0answers
54 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, ...
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1answer
55 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
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1answer
98 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 ...
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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
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0answers
44 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
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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
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1answer
57 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
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1answer
275 views

What is the difference between “loadings” and “correlation loadings” in PCA and PLS?

One common thing to do when doing Principal Component Analysis (PCA) is to plot two loadings against each other to investigate the relationships between the variables. In the paper accompanying the ...
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2answers
46 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
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1answer
53 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
56 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
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3answers
128 views

What is shallow architecture in machine learning?

What is a precise definition of shallow architecture in machine learning?
2
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1answer
30 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
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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
63 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
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1answer
262 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
3answers
240 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
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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
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1answer
37 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
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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
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0answers
29 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
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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
44 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 ...
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1answer
259 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.