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Questions tagged [discrete-data]

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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Comparing odds ratios of continuous and discrete variables

I need to compare the ability of two methods to predict an event with a binary response. Each method produces a score, where the higher score indicates 1 and a lower score indicates 0. I am looking to ...
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0answers
290 views

Computing the expected value using the sample mean gives poor convergence?

This is for Project Euler problem #371: http://projecteuler.net/problem=371 My solution was to generate a huge random pool of numbers between 0 and 999 inclusive, repeatedly ask the question 'How ...
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3answers
1k views

Set of numbers statistically higher than other

I have a set of numbers (number of publications for each year of one person). I don't know the exact distribution. Now I also have another set of numbers to compare that to (number of publications for ...
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0answers
264 views

Quantifying differences in a discrete distribution across several populations

Suppose you have a discrete random variable, $Y$, with a large number (say, $300$) of discrete (which happen to be nominal) possible outcomes. The mass function, $p(y)=P(Y=y)$, is unknown but a sample ...
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1answer
362 views

Discretize frequency of words that follow zipfian distribution

How could I discretize the frequency of words found in a corpus that follow a zipfian distribution? Are there standard methods? It should create bins of exponential-increasing size. My goal is to ...
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1answer
178 views

Correct approach to statistical analysis of voting results

Consider data consisting of voting results. Votes can be either individual votes of jury members or aggregated votes by certain communities (professional of geographical). In the end there is a set of ...
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0answers
345 views

Is it valid to model discrete numerical test scores as coming from a continuous random variable?

I'm working with a sample of test scores which range from 0 to 100. These scores are generated from a set of 100 binary responses (0 or 1), so the higher the resulting sum, the better the performance. ...
3
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1answer
218 views

Mapping discrete variables

Let's say I have a set of discrete, arbitrary variables sampled at continuous co-ordinates, e.g. ...
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0answers
180 views

Stopping rule for chi-squared discretization algorithm

I developed an algorithm that uses the chi-squared test to perform supervised discretization of a continuous variable. I described it in the paper "ChiD-A Chi-Squared Discretization Algorithm" ...
3
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1answer
835 views

Lower bound for tail of hypergeometric distribution

There are several simple and widely used upper bounds on the tail of the hypergeometric distribution, including $P(X > E[X]+tn) <= e^{-2t^{2}n}$, where X is hypergeometric with parameters N, M, ...
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2answers
8k views

Finding correlation of discrete distribution data

I'm not good at Statistics but I need to use it to summarize my case study. So I consult with a person who're good at Statistics. He suggested that My data is discrete because all the values are ...
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0answers
3k views

How to model categorical (discrete-valued) time series?

Just want to make a little survey, What are, according to you, the best approach to model categorical time series? I'm building a model able to generate time series reproduicing the characteristics ...
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2answers
5k views

What is the best way to discretize a 1D continuous random variable?

Say I have a 1-dimensional continuous random variable $X$, with PDF $f(X)$, CDF $F(X)$ and inverse CDF $F^{-1}$. What is the best way to discretize $X$? To keep things clear, let $Y$ denote the ...
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1answer
2k views

Determining an optimal discretization of data from a continuous distribution

Suppose you have a data set $Y_{1}, ..., Y_{n}$ from a continuous distribution with density $p(y)$ supported on $[0,1]$ that is not known, but $n$ is pretty large so a kernel density (for example) ...
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1answer
20k views

How to test if my data is discrete or continuous?

It seems to me that to choose the right statistical tools, I have to firstly identify if my dataset is discrete or continuous. Could you mind to teach me how can I test whether the data is discrete ...
7
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1answer
475 views

Multinomial choice with binary observations

Is there a standard name for a multinomial choice model where the observations are in the form of binary questions such as "do you prefer A to B" and "do you prefer B to D"? This seems like a common ...
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3answers
2k views

How to characterize symmetric discrete distribution?

I have a very basic question on when a discrete distribution might be called a symmetric distribution. Let say I have a r.v. $X$ that can take two possible values $(x1, x2)$ with $x1 \neq x2$ and ...
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0answers
209 views

Books for mixed distributions (continuous and discrete)?

What is a good book that covers mixed distributions? Most statistics books either only briefly mention them or do not cover the topic at all. I'd like to have a comprehensive resource covering ...
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1answer
3k views

Discrete functions: Confidence interval coverage?

How to calculate discrete interval coverage? What I know how to do: If I had a continuous model, I could define a 95% confidence interval for each of my predicted values, and then see how often the ...
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2answers
394 views

How to average quantized and truncated data?

So I have data that has been quantized by an analogue to digital converter. (continuous data has been turned into discrete data and the values range from 0 to the saturation value , which is 127 in ...
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3answers
9k views

Probability formula for a multivariate-bernoulli distribution

I need a formula for the probability of an event in a n-variate Bernoulli distribution $X\in\{0,1\}^n$ with given $P(X_i=1)=p_i$ probabilities for a single element and for pairs of elements $P(X_i=1 \...
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0answers
399 views

Averaged continuous Kernel Density Estimates in lieu of a discrete Kernel Density Estimate in Monte Carlo Proceedure

I am thinking of using this code in a Monte Carlo routine to generate Kernel Density Estimates for subsequent use in a Naive Bayes Classifier (see this earlier post). The author of the code states ...
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1answer
413 views

Sampling with unequal bins?

I have a very simple model. This model uses data that are not given as continuous distributions, but are described by percentiles. What is the best way to sample these percentile bins, when the bins ...
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1answer
718 views

All-Purpose Sample Entropy

When given samples of a discrete random variable, the entropy of the distribution may be estimated by $- \sum \hat{P_i} \log{\hat{P_i}}$, where $\hat{P_i}$ is the sample estimate of the frequency of ...
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3answers
7k views

How to test group differences on a five point variable?

I have a series of observations that fall into bins (or "scores"); that is, the data can be 0, 1, 2, 3 or 4. There are two groups of such data, control and treated. I know the number of individuals ...
28
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3answers
18k views

Is Kolmogorov-Smirnov test valid with discrete distributions?

I'm comparing a sample and checking whether it distributes as some, discrete, distribution. However, I'm not enterily sure that Kolmogorov-Smirnov applies. Wikipedia seems to imply it does not. If it ...
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1answer
316 views

To what extent can we call a Geometric Distribution a Geometric Density

In some papers, for example in "The Geometric Density with Unknown Location Parameter" by Klotz, a Geometric Distribution is called a Geometric Density. For me, this claim looks erroneous, however ...
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10answers
899k views

What is the difference between discrete data and continuous data?

What is the difference between discrete data and continuous data?