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).

Filter by
Sorted by
Tagged with
1
vote
0answers
82 views

How to fit a discrete distribution that can only be sampled from to count data?

My question is similar to this one. Assume we have a distribution from which we can only sample, but have no information on its pmf and consider further some count data: ...
0
votes
2answers
90 views

Measuring how well a new vote fits to a model of existing votes

My knowledge in statistics is very limited, so I hope this is actually an easy question. I am working on a kind of survey application where users either vote between a finite number of discrete ...
2
votes
2answers
429 views

Gibbs sampling and mixed distribution

For a project, I need to simulate from a joint distribution with both continuous and discrete variables that are dependent. The conditional distribution of any variable given the rest is known. I ...
2
votes
0answers
73 views

Bias of sample correlation for discrete distributions

Is there a proof showing the bias (or lack thereof) of the sample Pearson's correlation for discrete interval variables? In particular, I am interested in how such a proof handles the expected value ...
0
votes
1answer
374 views

Discretizing Continuous Outcomes: good examples?

My continuous dependent variable has a lot of error in it. Hence, I was thinking of discretizing it, to reduce the error for my modeling effort. But firstly, the main focus of my modeling effort are ...
1
vote
1answer
118 views

Combine Multiple Discrete Probability Density Functions

I'm a bit stuck trying to figure out the combined probability from several discrete PDF's. Lets say I have a bunch of different classes (Truck, Sports Car, Station Wagon, etc) and a bunch of ...
4
votes
2answers
4k views

distance measure of two discrete probability histograms (distance between two vectors)

I have multiple sets of discrete probability histograms(vectors) and I want to measure the distance between each histogram. I have done some research but I am in doubt. Literature suggest I could ...
0
votes
0answers
63 views

How would you correlate time series (price changes) to a discrete event happening?

I'm not sure what kind of model you would use here... But say you are looking at the price of the S&P 500. Suppose... If the market trends up, then everyone is happy and more likely to spend. ...
4
votes
0answers
140 views

How can I test whether an empirical discrete distribution is symmetric?

For example, I have a distribution with mean = 55.46; med = 54.5; mode = 45. The Shapiro-Wilk is non significant, the data are unimodal, and there is no significant skew or kurtosis. At a glance, the ...
0
votes
1answer
279 views

Discrete or continuous variable

I am trying to model Ip adress to cretae a fraud detection framework. So I am wondering if Ip Adress is a continuous or discrete or categorical variable. Bests
0
votes
0answers
25 views

Does it make to sense to derive a new column based on quantiles?

I am working with a dataset with alcohol levels. It looks something like this: Alcohol Level 10.34 3.21 323.12 ... I'm wondering whether it is common to "bin" ...
0
votes
1answer
27 views

computing P(a∧b) given P(a) and P(b) empirical distributions over 2D space

I know this is really basic but I have been unable to find anything to confirm or refute my understanding. Suppose two discrete, independent, empirical random variables $A$ and $B$ which are ...
1
vote
1answer
233 views

How to report a value determined from a cumulative sum?

I'm reporting on methods that use discrete distribution data, for example: ...
3
votes
0answers
438 views

Goodness-of-fit for Discrete Distributions

I've been doing some data analysis with Scipy. So far I accomplished this with continuous distributions: I can fit a probability distribution to a set of data points using a maximum likelihood fit. ...
6
votes
4answers
34k views

What are the variance and standard deviation for a standard six-sided die?

I'm having trouble imagining what variance and deviation mean with a series of die rolls. That is, a fair die will fall with a flat distribution on all its values 1-6. Does the concept of variance ...
0
votes
2answers
400 views

Calculate probability distribution table for dates

I'm a software developer. Over 10 weeks our team has had the following estimations/actuals for how much work we can complete in points: ...
0
votes
1answer
356 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 ...
0
votes
2answers
688 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 ...
0
votes
1answer
409 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 $\hat{N}=\...
1
vote
2answers
462 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 ...
11
votes
3answers
1k 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, $n$,...
5
votes
3answers
4k 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), and/...
2
votes
0answers
241 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. ...
1
vote
1answer
4k 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 ...
1
vote
1answer
440 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 ...
0
votes
1answer
363 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 ...
1
vote
1answer
104 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'...
1
vote
0answers
683 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
votes
1answer
28 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 ...
1
vote
0answers
83 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 ...
4
votes
1answer
194 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 ...
1
vote
0answers
26 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 \...
1
vote
1answer
101 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 ...
2
votes
1answer
135 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 ...
0
votes
1answer
14 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 ...
6
votes
1answer
453 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 ...
1
vote
1answer
177 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 $X^2$?
1
vote
0answers
20 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 ...
5
votes
2answers
1k 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 ...
3
votes
1answer
335 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.
2
votes
1answer
582 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 ...
0
votes
2answers
365 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 ...
1
vote
0answers
150 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, ...
1
vote
1answer
1k 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, ...
1
vote
1answer
798 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. ...
1
vote
0answers
293 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 ...
9
votes
4answers
1k 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 ...
1
vote
2answers
711 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 ...
2
votes
0answers
128 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) Incremental (...
4
votes
2answers
6k 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 ...