Questions tagged [continuous-data]

A random variable $X$ is called continuous if its set of possible values is uncountable, and the chance that it takes any particular value is zero ($\text{P}(X = x) = 0$ for every real number $x$). A random variable is continuous if and only if its cumulative probability distribution function is a continuous function.

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What statistical model can incorporate my categorical variable (2 levels) and 2 continuous variables?

I have some data which has a categorical variable (treatment) with 2 levels, control and 'mice added'. I have 2 continuous variables of plant density and elephant number/density. I have examined the ...
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Statistical testing on discrete time series data?

I am trying to analyse some data which has 40 different subjects, 1 categorical factor with two levels (20 male and 20 female). The rate of tree cutting was recorded at 4 different time points for ...
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Ranks of a set of maximal invariant statistics

Let $\{\mathbf{x}_l\}_{l=1}^L$ be a set of i.i.d. (continuous) random vectors sharing the same density $p_X$. Let $\{Q_l\}_{l=1}^L$ be a set of (positive and continuous) random variables representing ...
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Finding an association between two methods of medical intervention and a continuous variable [duplicate]

I have here with me, two methods of intervention; a standard care method, and a specialised intervention. Different individuals receive different method, its all randomly allocated. I am trying to ...
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Continuous predictors for negative binomial regression

I can't seem to find a straight answer for this question. From formal coursework I've taken, it seems that Poisson/negative binomial regression require a data layout like this: Where the categorical ...
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How to make a choice when there is doubt between a variable being categorical or continuous?

I have an instagram dataset. Often the caption contains tags (@person_x). I counted the amount of tags per post but now can't choose wether to use it as a continuous variable or categorical. I know ...
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Accounting for Inter-Sample Collection Time Variability

I'm trying to run regression analysis on a dataset that features a pair of continuous variables that are collected at a certain time (in days). Whilst the data should be collected at a specific time, ...
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multivariate analysis with mixed numerical and categorical dependent variables

I have one independent variable (yes/No) and several covariates (sex/age and so on..), five dependent variables (four continuous, normal distributed and one categorical as yes/no). I want to look up ...
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Data analysis method for 1 independent variable and several dependent variables?

I am working on a fertilizer experiment, involving three different treatments of fertilizer. I wish to evaluate the relationship between the treatments (independent variables) with several different ...
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Can I treat my continuous variable as a categorical variable?

I know that there many dangers and disadvantages of treating a continuous variable as a categorical variable. However, I also read in some cases it is applicable (e.g. when the relationship is non ...
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Positive sums of small quantities at low resolution

Many measured continuous quantities are in fact sums of discrete events measured with insufficient resolution (e.g. electric current) and thus conveniently modeled by continuous probability ...
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Best way to establish effect sizes in high-dimensional model with mixed data

I have 4 categorical variables, one is by state so it has 50 possible values. I also have 3 continuously distributed values. I'm trying to predict a continuous variable. I'm using a random forest for ...
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Which statistical test to use for one continuous dependent variable and 2+ continuous independent variables?

I am exploring the relationship between unemployment (using unemployment rate, continuous dependent variable) and migration flows (continuous independent variable) over time. I have done a series of ...
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On continuous random variables

Mia breaks glasses at the rate of 4 per week .Let t be the time in weeks between successive breakages of glasses .Then: $f(t)= 4e^{-4t} \quad \text{when} \quad t\geq0 $ $ 0 \quad \quad \quad \...
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Which test is suitable in below situation?

I want to calculate the correlation of two continuous variables, unfortunately both of them are not normally distributed. (by using Shapiro-Wilk test) There are two categorical confounding variables ...
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How to treat low frequency continuous variable in machine leanring

Hello I am working on machine learning model for count data, and I have various features that are highly skewed. The frequency table for one of the feature is given below. ...
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Specification on power spectral density for population data

What is the best way to put a specification on the single-side auto-power spectral density (PSD)? We have a product for which we have a time signal. For this signal we calculate the PSD (or ...
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Estimating a logistic regression with OLS? [duplicate]

NB: This question is different from this one which assumes that we have computed the LHS of the regression equation with no issue. My question is about how to compute this LHS. Consider a simple ...
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1answer
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Determining best cutoff value between 2 groups

I have 2 groups (say G1 and G2) and there is a continuous variable (say V) which is significantly different between 2 groups. The mean values for 2 groups are m1 and m2. I want to determine what is ...
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Why probabilities are measured over intervals (instead of points) for continuous probability distributions? [duplicate]

In case of discrete probability distributions, we find probabilities of different points/values over exactly those points, but in case of continuous probability distributions, we find probabilities of ...
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Does treating trial number as a continuous variable for linear models lose information?

If I create a linear model where Trial number is one of the predictors, am I losing any information by treating it as continuous (when in fact it is actually discrete + ordinal)? I believe the answer ...
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diff-in-diff with continuous treatment vs cut-off point (and 2 periods)

I have panel data for a number of counties for two years only (t = 1,2). The treatment, let's assume it's a policy implementation programme, happens in between year 1 and 2 and it is a continuous ...
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What is the best test to compare two sets of continuous data to see if they differ at each pair and overall?

I have two sets of data comparing the mean consumption of 4 materials before and after a new production standard have been introduced. i have 4 different materials and the consumption of each one is ...
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analysis of variance on zero inflated semi continuous data

I have a fairly fundamental problem with my data, they do not suggest that they were sampled from a normal distribution. This is problematic because I would like to run some sort of analysis of ...
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Discrete weather data causing issue in predicting spatial yield

I want to incorporate the weather data into predicting spatial yield. Major data used: 4 years spatial yield data from a 10-ha crop field 4 years of daily weather data such as rainfall from a ...
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1answer
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X given Y is a normal random variable with mean Y and var 4. Y~Binomial(10, 0.6). Find E(X) and Var(X)

Is this a joint probability distribution? Can I assume X and Y are independent and that E(XY)=Y? I am stuck at this question.
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Machine learning on Percent as dependent variable [closed]

I am working on a problem where I am tasked to predict users into 'High users' and 'Low users'. Dependent variable provided is in percent of orders (%) which is calculated as (#orders placed/#sales ...
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Normal V Binomial Distribution (Elementary Question)

CONTEXT: First year university statistics course exam question Suppose couples decide to have children until they either have a child of each sex, or they have three children. Assume that births are ...
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How to treat missing values in a continuous variable?

I have a classification problem and I am doing the data analysis. I came across a variable which is numeric continuous and have some missing values. I checked the missing values and are real missing ...
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Best approach for dealing with continuous predictors with missing data in random forests

I was thinking about a problem I'm facing: I have wage data that I want to add to my model, but it's incomplete (data for about 70% of my observations). So, I was ...
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1answer
154 views

Is there a Continuous Conditional Variational Autoencoder?

Conditional Variational Autoencoders (CVAE) are an extension of Variational Autoencoder (VAE). In VAEs we have no control on the data generation process, something problematic if we want to generate ...
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Continuity of the joint CDF

Consider two random variables $(X,Y)$. Suppose that the joint cumulative distribution function (CDF) of $(X,Y)$ is continuous. Is it true that this implies: 1) The CDF of $X$ is continuous? 2) The ...
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How to make SalePrice as a discrete value?

The target variable, Saleprice originally is a continuous value. I calculated ...
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how entropy works in continuous distribution using the K nearest neighbour?

So calculating entropy in continuos distribution was developed by Kozachenko and Leonenko (1987). I have seen one implementation here. however I have problem understanding the approach. basically, ...
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1answer
129 views

How to model a zero-inflated 'continuous' response data in r 'without' assuming an underlying normal distribution?

I have a weather data set with rainfall as response. It has 56% observations as 0, while the rest as continuous rainfall data. I can't use tobit, hurdle or any other zeroinfl() model as they require ...
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Is there a standard name for this continuous distribution? [closed]

I'm encountering the following PDF of continuous scalar real $X$ with semi-infinite support $]0,+\infty[$: $$ f_X(x) = C ~ x^{-\alpha} ~_1F_1\left ( a,b;-\frac{d}{x^\beta} \right ),~~~~~~\beta>0;~\...
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Repeated measures design (2x2 within subject variables) with one continuous variable and one covariate

I have a repeated measures design (one DV measured twice, both times in two different conditions) with one continuous IV and one (continuous) covariate. I'm trying to see if there is an interaction ...
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Estimate total effect of treatment when continuous treatment variable and its dichotomization show contradicting impacts

I am trying to estimate the total effect of a leak of a harmful gas on my dependent variable. While I do not know the actual exposure, I know the distance of a household to the origin of the leak in ...
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Why is the Cauchy Distribution so useful?

Could anyone give me some practical examples of the Cauchy Distribution? What makes it so popular?
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1answer
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Conditional survival probability up to time $T$ given $t > s$

This is a really basic question I know but for some reason I'm failing to convince myself of the right answer here. Given a survival model that has CDF $F(t) = \mathbb{P}(\text{failure before}\ t)$ ...
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1answer
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Explanation of multiple linear regression output

Just looking for some help with the interpretation of my multiple linear model output and also some validation on the methods I used. I have 1 response - Ball speed and 9 continuous predictors and 1 ...
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is there a difference between E[e|x]=0 and E[e|d=1]-E[e|d=0] in continuous vs discrete case in regressions?

in the discrete case, if assignment is random, then i can express E[y|d=1]-E[y|d=0] = B + E[e|d=1]-E[e|d=0], where the expectation of the errors are the same for both groups and become zero. Where I ...
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61 views

How to choose sample size from probability density for computing mutual information based on continuous variables

I need to compute mutual information gain based two continuous variables $X$ and $Y$ $I(X|Y) = \int_X\int_Y p_{x.y}(x,y) \log(\frac{p_{x.y}(x,y)}{p_{x}(x)p_{y}(y)})$. I have used Kernel Density ...
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Conditional probability formula for continuous random variables [duplicate]

Let $V,T$ be two random variables with supports $\mathcal{V},\mathcal{T}$, respectively. Let $P_{V|T}$ denote the probability distribution of $V$ coditional on $T$ $P_{V,T}$ denote the probability ...
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Application of law of total probability for continuous random variables

Consider 3 random variables $Y,V,T$, with supports $\mathcal{Y},\mathcal{V},\mathcal{T}$, respectively. Let $P_{Y,V}$ denote the probability distribution of $(Y,V)$ $P_{V}$ denote the probability ...
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Are multicollinearity an issue for continuous variables only, and maybe ordinal variables, but not for nominal variables?

To avoid multicollinearity, correlation analysis can be conducted between variables. Some applicable tests for correlation measurement are Pearson's correlation. Spearman's rank correlation. ...
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Clustering Binary and Continuous Features

If you need to cluster a dataset with the following characteristics: It has a mix of binary and continuous features. It is very sparse. For most features, you only have values for 15% of the ...
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What does “density” really mean in probability density function in statistics? [duplicate]

I am familiar with the concept, but I simply can’t get my head over the intuition behind it. While being a derivative, it describes the rate of change for one unit. Simply put, we can say that it ...
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Correlation between discrete and continuous data

I would like to caculate the correlation between two vectors. One vector represents the intensity of an emotion as continuous data between 0 and 100. The other vector represents the intensitiy of an ...
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1answer
52 views

Can a discrete random variable be absolutely continuous of a continuous random variable?

I have a question in measure theory: given two measures $\nu$ and $\mu$, we say that $\nu$ is absolutely continuous of $\mu$ if for Borel set $A$ such that $\mu(A)=0$, we have $\nu(A)=0$. I want to ...