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).

learn more… | top users | synonyms

2
votes
2answers
41 views

Mean Preserving PDF Spreading

I have a histogram representing the PDF of an unknown discrete RV. The histogram is asymmetrical. To be clear, all I have is the histogram. Is there a known way to increase/decrease the variance of ...
3
votes
2answers
69 views

how can I test if a sample was created from a specific Discrete Distribution

How can I test if a sample was created from a specific discrete distribution. For example, if I have the following distribution 1- 0.2 2- 0.5 3- 0.3 and I ...
0
votes
0answers
15 views

Test if 2 samples are taken from the same population (multi-dimensional data) - worked example

I'm looking to learn (not just apply) how to test is two samples are drawn from a single population. The data I'm likely to apply this to is multi-dimensional so that's my target. Can anyone give me a ...
1
vote
0answers
21 views

hypothesis test for discrete disributions

I am interested in the number of instances of feature $F$ among the members of two populations, $A_1$ and $A_2$. e.g. $F$ is a some special genetic element that may occur several times within a ...
1
vote
0answers
7 views

What is the discrete equivalent to the 4-plot?

Quoting NIST, when analyzing a continuous variable, one needs to validate four assumptions that typically underlie all measurement processes; namely, that the data at hand "behave like": random ...
0
votes
0answers
14 views

Simulate birth with Rstudio - draw pmf and cdf [migrated]

I have a little exercise to solve with Rstudio for my statistics exam. I tryed to translate it in english, so if something isn't clear please ask me for explanations. "Simulate 100,000 births and use ...
4
votes
1answer
267 views

Why is this random variable both continuous and discrete?

The waiting time, $W$, of a traveler queuing at a taxi rank is distributed according to the cumulative distribution function, $G(w)$, defined by: $$G(w) = \begin{cases} 0 & \text{ for } ...
4
votes
1answer
42 views

Question about the the median and the mode in skewed distributions

In intro statistics textbooks, the mode is typically described as least susceptible to skewness, followed by the median, which is in turn followed by the mean. The difference between the median and ...
0
votes
0answers
22 views

Finding n and c in single sampling plan

I am learning a quality control course and in Single sampling scheme for attribute type inspection I don't understand the method used for calculating the values of $n$ and $c$. The method is as ...
0
votes
1answer
32 views

Chi-squared two sample test for unbinned discrete data

I am wandering through the net but I cannot get a precise description of how to solve this simple task. Two sets of datas ...
2
votes
1answer
61 views

Number of different combinations in a sample

I hail from Mathematica SE. A friend of mine asked me a statistics question (I'm an economist and am assumed to know such things) which kind of stumped me, since I usually deal with non-discrete ...
0
votes
0answers
13 views

Monitoring high quality near zero defect processes

What are the latest techniques for monitoring discreet defects in high quality processes with defective rates in the parts per million range?
2
votes
0answers
25 views

Discrete Choice Models

for mulitnomial (or mixed) logit models, when the choice set is too large, either strategic sampling or random sampling of the choice set can be used. My question would be: Is that also true in ...
3
votes
0answers
26 views

Estimating a probability distribution with a discrete and continuous part

This is a question more for advice and a suggested starting point than anything else (though anything else is cool as well ) The data that I have is something like this - 1,000,000 data points of ...
6
votes
2answers
143 views

5 defectives rule of thumb

I have taught six sigma black belt classes using consultant sourced training materials which included the rule of thumb that when estimating the rate of occurrence of discrete events, like the ...
1
vote
1answer
63 views

Calculation of Higher-Order Cross-moments

How can I calculate standardized central cross-moments for 2 time-series? The 4th-order standardized central moment, kurtosis, is; ...
-1
votes
1answer
74 views

Median and mode

Consider grouped data with frequencies and more specifically data that are discrete. If I have for example different xi with the same frequencies, what is the right answer: there is no mode or all ...
1
vote
1answer
102 views

Power-law fitting and testing

I want to test the distribution that best fit a specific metric (that I call SD) extracted from the source code of systems. I have a guess that they follow a power-law behavior. My sample: 20 ...
0
votes
1answer
33 views

Discrete Variables and Regression

I have only discrete independent variables (gender, religious affiliation etc) and continuous dependent variables. Is it possible to use a regression model?
1
vote
0answers
19 views

How to compare a one-day count against a historic mean to identify an external change

A few months ago a client's website had some good press and their daily site visits spiked. Now, every time their traffic shows a bump, they think something external has caused it to happen. I'm ...
1
vote
0answers
17 views

Transforming data with a limited range (0,1,2) for parametric testing (ANOVA) [duplicate]

I've collected data on accuracy of recognition of images. Accuracy is a score out of 2 with points 0,1,2.. participants can score a 0. I am aiming to use a parametric test (ANOVA mixed design) to ...
0
votes
0answers
15 views

MNL discrete choice with quasi-SUR 4 equation system, looking for R package that can handle such a system

I am attempting to recreate the model in this paper: Pinjari (2011) in which the author uses a 4 equation system with discrete choice dependent variables in each of the 4 equations. Does anyone ...
1
vote
1answer
171 views

Can I still interpret a Q-Q plot that uses discrete/rounded data?

I have a data set with only discrete/rounded values in it. As a result, when I produce a Q-Q plot a "stair-case" pattern appears. Can I still interpret this just like a normal Q-Q plot even though it ...
0
votes
1answer
31 views

Correlation or clustering of continuous score and discrete variable states

I have an experiment that produces a decimal score representing quality, and a bunch (5-30) of variables that each take on one of a set of discrete states. - The states are not meaningfully ...
0
votes
0answers
47 views

Clustering method that can use graph links, discrete and continuous properties?

I have an un-weighted, directed graph that clusters ok using MCL or other graph clustering algorithms. However, I also have additional discrete and continuous properties of the nodes being clustered ...
1
vote
1answer
397 views

Plot the probability mass function

I am trying to plot the probability mass function of a sample of a discrete metric. If it was continuous, I know that using pandas it would be as simple as calling: ...
1
vote
0answers
29 views

How can I smooth a set of discrete data points for the purpose of schedule planning?

Disclaimer: I do not have a background in statistics or the math behind filtering, save one long-time-ago college course. I have a well defined problem space. I am calculating hourly staffing ...
1
vote
0answers
29 views

What model to classify a discretized continuous variable

Consider a variable $y$ (typically, $y_i$ is something like number of inhabitants of city $i$) and some given features $X$. Let us assume that these features are continuous (eg. total city area, ...
0
votes
0answers
50 views

How to use Hartemink's discretization algorithm?

From the help documentation of the discretize function of the R package bnlearn: Hartemink's algorithm has been designed to ...
6
votes
1answer
254 views

Question about Dynkin Lehmann Scheffe Theorem

I'm self-studying for an examination, and I would like to understand how to use the Dynkin Lehmann Scheffe theorem for an applied question. I am using Bickel and Doksum's "Mathematical Statistics" ...
0
votes
0answers
54 views

Can Principal Component analyses be applied to a counting trait?

I am analyzing a segregating population of plants coming from an hybridization process. The experiment consists in several field plots (according to an augmented design). In each plot a segregating ...
2
votes
1answer
220 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 ...
0
votes
0answers
30 views

Conceptual question on image pattern representation

I have a basic question regarding pattern learning, or pattern representation. Assume I have a complex pattern of this form, could you please provide me with some research directions or concepts that ...
8
votes
4answers
1k views

Calculating PDF given CDF

I know that the PDF is the first derivative of the CDF for a continuous random variable, and the difference for a discrete random variable. However, I would like to know why this is, why are there ...
0
votes
1answer
46 views

Correct notation wrt. uniform distribution

Assume that I have a discrete set $L$ and a transformation $\phi: L \rightarrow [0,1]$ that normalizes set $L$ such that now values belonging $L$ are uniformly distributed among the unit interval. ...
2
votes
0answers
37 views

expectation of multivariate discrete distribution

The expectation of a function $f(x)$ over a probability distribution $p(x)$ where $x=(x_1,\dots,x_n)$ and $x_i \in \left\{1,\dots,K\right\}$ requires a summation over all possible $K^n$ combinations. ...
2
votes
0answers
48 views

deterministic sampling for multivariate discrete distributions

Unscented transform can approximate expectations well via deterministic sampling. if $f(x) = N(\mu,\Sigma)$ and $x\in \mathbb{R}^d$ then $\int f(x) h(x) \approx \frac{1}{2d}\sum_{i=1}^{2d} h(x_k)$ ...
1
vote
0answers
70 views

Conjoint analysis or discrete choice analysis ? And which software?

Suppose I would like to model the light-bulb preference of respondents. I would like to ask their preferences between existing bulbs on the market. And when you choose a bulb in a shop you usually see ...
0
votes
0answers
57 views

Which contingency method to use with a 3x3 table yet still account for expected or discrete choice?

Im not sure what test to conduct when I have 3x3 matrix of data and still account for availability. So, in a simple chi square you have an observed observation and then you are often able to ...
2
votes
1answer
121 views

Hazard and density function in survival analysis with discrete time

I am running a survival analysis with descrete time. For that purpose I use the R package survival with this function ...
1
vote
0answers
71 views

A good alternative to data binning?

I read many times that data binning of continuous variables is a very bad idea. For instance, let's take something like heart rate and let's define the following 2 bins: (125 - 135), (136 - 145) ...
0
votes
0answers
155 views

Analyzing discrete choice panel data with mlogit in R

I searched around and saw some high level discussion on mlogit and discrete choice panel models (here and here) but I need a more concrete answer than those. I am hoping somebody can point out what I ...
-1
votes
1answer
70 views

Find the maximum likelihood estimator of $\theta$

Let $(X_1,Y_1), . . . , (X_n,Y_n)$ be a random sample from the discrete distribution with joint probability mass function $$ f_{X,Y} (x,y) = \frac{\theta}4 , \space (x,y) = (0,0)\space or ...
3
votes
1answer
162 views

Bayesian Networks and discretization of variables using K-means clustering

In many approaches to learning Bayesian Networks a solution to tackle continuous variables is to discretize them and apply one of the well established techniques for learning Bayesian Networks ...
2
votes
1answer
47 views

Distribution of MLE of $N$ based on a random sample of size n from discrete uniform dist.(1,2,…,$N$)

Let $X_1, X_2, ..., X_n$ be a random sample from discrete uniform distribution on $(1,2,\ldots,N)$, where $N$ is an unknown positive integer. Find MLE of $N$ and also find the distribution of the MLE. ...
1
vote
1answer
126 views

Uniform sampling of a set of weighted samples

Consider a two-stage sampling scheme: First, use weighted random selection from a list to obtain a set of N unique elements. Next, use uniform random selection to pick one of those elements. How can ...
0
votes
0answers
79 views

POISSON regression with offset variable

Our problem is to determine if there is a relationship between the return on equity of firms (ROE) and the presence (number of indicators used) (Y) of a specific type of indicator showing up in the ...
1
vote
1answer
28 views

How to test if a value is over-represented in one sample vs another

I have two multinomial data samples that both have N discrete categories. I know that a Kolmogorov-Smirnov test will let me know if the distributions of the two ...
2
votes
0answers
36 views

Metric optimization on discrete learning sample

There are a set of ("artifical") not Minkovski (triangle inequality is not guaranteed) metrics defined on set of objects. There are one etalon ("natural") metric, which estimation is known only for ...
3
votes
2answers
262 views

How to decide on the MLE when pmf is 0?

Suppose you have $\theta=\{1,2\}$ and the sample of (0,1,2) with the task of finding MLE: \begin{array} {|c|c|c|} \hline x & p(x|\theta=1) & p(x|\theta=2) \\ \hline 0 & 1/2 & 1/4 \\ ...