Refers to data generated from a distribution that has a countable sample space. Discrete data may be nominal (e.g. the distribution of race in a sample of individuals) or ordinal (e.g. the number of errors on a page of text).

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3 views

Discretization for a bayes network model with small sample

I have been playing around with a Bayesian network toolbox for prediction and classification. I have had good success with the examples but I'm now stuck on how I should proceed with my scenario. I ...
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1answer
30 views

Exploring the relationships between discrete and categorical data

When you want to test the relationship (correlation) between two continuous variables, the main methods are easily learnt and very well documented. Scatterplots with regression lines, pearsons ...
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2answers
26 views

Methods for modeling discrete dependent variables and categorical independent variables

I need to determine if there are relationships between discrete dependent variables and categorical independent variables. To give some examples, one discrete dependent variable would be salary and ...
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20 views

How to compute a mean of some numbers from normal distribution? (using continuity correction) [closed]

In practice, specifically writing a paper, we often need to compute an expected value of some sample drawn from a certain continuous distribution. Let's say, draw 100 numbers from $N(0,1)$, and ...
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1answer
48 views

MLE for discrete uniform distribution [closed]

I am trying to find $N$ by MLE for several discrete uniform distributions involving a parmeter $N\in \mathbb{Z}$. If the interval $X$ is defined on is $X\in (N,N+1,...,N+10)$ then I think ...
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2answers
43 views

Probability distribution of rare condition count

A population of t=310M experiences an environmental change that causes one in s=112M of them to acquire a particular condition c, each one independent of the others. What is the probability p that ...
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3answers
216 views

Visualize bivariate binomial distribution

Question: what does a bivariate binomial distribution look like in 3-dimensional space? Below is the specific function that I would like to visualize for various values of the parameters; namely, ...
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2answers
70 views

Comparing two (or more) discrete distributions

I would like to know what the most powerful way of comparing two (or more) discrete distributions is. I know that the Kolmogorov-Smirnov test could be used (if corrected for the discrete ecdfs), ...
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0answers
69 views

Combining Bhattacharya Distance (or A Measure of Similarity) — across Different Variables (Properties)

We have a series of observations of different properties (such as heart rate or blood sugar level and others as well) across different days from different people from different geographical regions. ...
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1answer
72 views

chi-squared with too many degrees of freedom

I have a third party random number generator with a period approximately greater than $63*(2^{63} - 1)$ which generates numbers in the range $[0,2^{32}-1]$, ie $2^{32}$ different numbers. I've made ...
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1answer
28 views

Is it better to use the original continuous or discretized data in building a model?

I am currently competing in a Kaggle competition and wondering is it a good choice to discretize particular variables. I saw that some specific continuous variables have almost all values that are ...
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1answer
31 views

Throwing two four-sided dice; min/max problems

Suppose two four-sided fair dice. Let $X = min(X_{1}, X_{2})$ and $Y = max(X_{1}, X_{2})$ where $X_{1}$ is the result of the first dice and $X_{2}$ the result of the second dice. What is the PMF of ...
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1answer
21 views

multiple comparison for discrete nonparametric distributions

I have N=24 controls and M=10 patients. (M can be 20 later) Each subject has one 3D image, each element of the image is a discrete value (integer) ranging from 0 to 4 [0,1,2,3,4]. It's like a score. ...
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0answers
16 views

Is there a proper interpretation of ordered multinomial variables in binomial Logit model?

I am using a binomial Logit model to make inferences about how respondents of a survey use the Internet based on differences in their financial well-being and income. My dependent variable measures ...
2
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0answers
42 views

Error introduced by rounding values from a continuous distribution

I am implementing a sampling routine to sample from a discrete normal distribution. I use a standard technique for sampling from continuous normal distribution and then round my values. If I am ...
2
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1answer
24 views

Given no knowledge of var, include both continuous and dummy

Imagine we have a variable with 5-7 unique values in a machine learning setting. One could argue that given no knowledge, we might convert it into 5 dummy variables, or one might consider it ...
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0answers
20 views

Statistics test for paired data with discrete outcomes

I have pre-post data for several variables and I'm looking to analyze them. The responses to the questions are 0,1,2,3,4 with 4 being best and 0 being worst. For each variable could I simply find the ...
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1answer
38 views

Efficient computation of the distribution of a weighted sum of finite discrete random variables

I have $N$ discrete random variables $X_i$, with distributions $p_i(X_i)$. $X_i$ can take integer values in a finite range $[a_i,b_i]$, where $a_i,b_i$ are integers. The distribution $p_i(X_i)$ is ...
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9 views

Joint cumulants of Zn2 characters

Let $f_{c}:Z_2^n \rightarrow \{-1,1\}$ be the character defined as $f_c(x) = (-1)^{<x,c>}$, where $c,x \in Z_2^n$. It is easy to see that since $f_{c_1}\cdot\ldots\cdot f_{c_k} = f_{c_1 \oplus ...
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1answer
35 views

Test for significance with multivariate, highly-skewed, discrete data

The data The dataset comprises 10 variables: waiting times (rounded to minutes) for questions to be answered on Stack Overflow by programming language. Each is discrete, none is normally distributed ...
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1answer
80 views

Plotting PMFs and PDFs

This is probably a silly question, but I was reading Computational Statistics with Python and there are a few plots describing prior, likelihood and posterior distribution in the context of ...
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1answer
12 views

How to combine a continuous effect into a function that is for discrete outcome

I have a function like this: log (P(1)/P(0))= a+ sum(h(x))+ g(x), where a is the intercept, h(x) is a binary outcome: 1, or 0. g(x) is a continuous variable that contribute to the log of a ...
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1answer
286 views

Continuous probability distribution over integers?

I have a random variable which can have any value from the set of natural numbers. For example, the probability of the random variable having a low value is higher than the probability of the random ...
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1answer
35 views

Transformation of variables in Poisson distribution

If $X$ is a random variable which follows $\text{Poisson}(u)$ distribution then what is the variance of $X^2$?
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10 views

Two-dimensional discrete aleatory variable prediction

I hope someone can help me a bit facing this problem. I have many item samples from a database (let's say 1000 for example) with two attributes: a price from a range of possible prices (0 to 8000€ for ...
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2answers
67 views

Notation for possible values of a random variable

Let $X$ be a discrete random variable that can take the values $1, 2, \textrm{and}\ 3$. What is the conventional way to write this mathematically? Is it just $X\in\{1,2,3\}$ or should I somehow write ...
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1answer
51 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.
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95 views

How do you derive AIC and BIC for discrete-valued observables?

Let's say I have an experiment which yields discrete results between 1 and $N$. I am modelling the results using a number of statistical models and want to use Akaike (corrected) or Bayesian ...
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0answers
24 views

Interpreting elasticity of dummy variable

This is a follow-up of my previous question. I post it as a new one since it has a different focus and may be interesting for other folks. I've read that elasticities of dummy variables are not ...
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1answer
53 views

Question about discrete, numerical data

True or false: In a survey of your neighbors (asking for family size, the kind of pets they have, the grade of the youngest child in the family, the family's annual income in dollars, what the dad ...
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28 views

Problem on Clustering Discrete Input using GMM

I want to do clustering using Gaussian Mixture modeling (GMM) on a set of data which is a 5-dimension vector of real values $(x_1,x_2,x_3,x_4,x_5)$. However the clustering result were pretty bad, ...
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1answer
44 views

When would one pre-specify thresholds in SEM/CFA for limited dependent variables?

I'm working on a structural equation model with limited dependent (discrete) variables using lavaan (0.5-17) in R (3.1.2). I have found that if I define the thresholds for the categorical variables, ...
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7 views

How can I make a correlation in SPSS about variable 1: discrete data (amount of people), and variable 2: nominal data (white, black, hispanic)? [duplicate]

I have 3 variables: var1: sex; var2: amount of people; var3: race (white, black, latino, etc). My population data is already coded. How can I establish a correlation between sex and race; or amount ...
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14 views

Spearman correlation for discrete tied data in relation to continuous variable?

I want to correlate tied discrete data- reward reimbursement having only 4 reward values with continuous variable- RT performance. Can I use the Spearman rank correlation or Kendall´s tau? Thanks.
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1answer
43 views

Estimate range of values of continuous variable corresponding to every level of discrete variable

This might seem a silly question, but I have Googled in vain for hours to find an answer, so here goes: I have two variables measuring the same physical parameter. Let's call these variables A and B. ...
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60 views

Regression Discontinuity on Stata with a discrete assignment variable and excluded data at the cutoff

I am looking at a treatment effect of an intervention on a cutoff of age, where age data is only available discrete as year of birth. Due to this, people who turned the cutoff age during the study ...
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13 views

Distribution of Augmented Random Variable

Consider the case where $\mathbf{X} = (X_1,...,X_m)$ has discrete-valued elements and distribution function $F(x) = C(F_1(x_1), ..., F_m(x_m))$. Let $F_j(x^{-}_j)$ be the left handed limit of $F_j$ ...
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4answers
393 views

Does an urn's probability distribution change as you draw from it without replacement on average?

Suppose I have an urn containing N different colours of balls and each different colour can appear a different number of times (if there are 10 red balls there need not also be 10 blue balls). If we ...
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2answers
69 views

Translating and scaling a uniform discrete distribution?

Is it possible to map a uniform, discrete distribution over two integers $A$, $B$ (lower and upper bounds respectively) onto $[A^*, B^*]$ while keeping the distribution discrete uniform? We may assume ...
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0answers
34 views

Multivariate discretization method / library for huge data

Does anyone know any multivariate discretization method that can be used for large amounts of data. A library / Python library would be awesome but algorithms would also do. Also I'm not sure if ...
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0answers
20 views

Goodness of fit test for binned multi-sample data

Let's say I have two samples and 5 bins. In each bin, I have a (positive) value and a measurement error on that value for each of the two samples. The value and corresponding measurement error ...
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0answers
18 views

Comparing Peptide Amino Acid Composition: 2 Independent groups, Non-normal data, discrete data

I have two large groups of peptides, "positive" group (n = 368) and "negative" group (n = 880). The average length of the peptides (in each group) is about 20 amino acids. What I am trying to do is ...
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14 views

Question on Texture similarity measures

I was wondering whether there is a similarity measure between a discrete image or texture image and a continuous image? I have two images one is discrete (it can be a texture also) and the other is ...
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0answers
97 views

Unified Variable Classification

I am trying to go beyond Stevens' Level of Measurement Typology. Here is what I have so far: Discrete Variables Nominal (like Apple, Banana) Ordinal (like 1, 2, 3) Count (like 0, 1, 2) ...
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1answer
159 views

Explanation of the different variable types in statistics?

One thing that has always tripped me up when trying to learn new methods in statistics is understanding what type of features/variables can this method be applied to. The variable types that ...
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2answers
66 views

Conditions to be a Joint Discrete Distribution Function

I am reading a paper on modeling the dependencies in discrete distribution functions, and am having a hard time understanding the following. Let us define: $$r \leq min(p,q)$$ $$ B(u,v) = ...
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1answer
245 views

How to normalize mixed continuous/discrete features for DNN?

I have had some success training my deep neural network (with ReLU hidden units) by first normalizing the features of my data set to zero-mean-unit-variance. Each sample of my data set has 600+ ...
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7 views

generating discrete distribution comparison score

I have constructed a distribution of some data that I am analyzing, so it is discrete, and I would like to be able to compare it to other distributions in order to generate a score or rank so that I ...
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0answers
22 views

Set probability of Discrete Random variable

I want to simulate outcomes of 3 discrete events. For example lets say I have a spinner and there are 3 outcomes. The outcomes of the spinner are 3 numbers: 1, 2 and 3. The probability of getting ...
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2answers
152 views

Model for comparison of two subsets of the same data

I am looking to perform an analysis on a subset of the data and compare it to a larger subset. My data is primarily categorical and the dependent variable is binary. I want to compare $y^*= \beta ...