# Tagged Questions

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 ...

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### Probability distribution estimate of target continuous variable

I am looking for litterature/reference on algorithms for a regression task that can give the probability distribution estimation of the output variable, or multiple outputs with their respective ...
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### Association of qualitative and quantiative variables

I have data of an ordinal qualitative variable and I would like to study if it has some relation with a continuous quantitative variable and I don't know what technique could I use for that. I was ...
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### Data preparation of a new record on the fly [migrated]

I am facing problem in the implementation of Data Preparation of a single record on the fly. I am loading the model from disk and I need to to make prediction against it. Lets Say, I have 3 ...
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### Neural Network - Multiple discrete and continious inputs

In order to keep the distance between discrete values irrelevant we often use one-hot encoding feature vectors to normalize our feature vector. So a discrete value could be splitted up into a number n ...
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### Negative binomial regression: control variables

Question: what are the assumptions of a negative binomial regression? Do continuous control variables (the DV and main IV are binary) need to follow a normal distribution? I have been searching online ...
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### Data type ontology naming: continuous

In one part of my API, I have an hierarchical ontology of data types declared: ...
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### Hard question - Trying to predict one dependent, continuous variable in 2 conditions, both with different correlations, how do I proceed?

I'm trying to explain the variance experienced with cybersickness, roughly put a type of motion sickness experienced inside of Virtual Reality (more specifically, I put participants in a virtual ...
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### Dummy coding vs. continuous variable in regression analysis

I am doing a regression analysis in R, in which I examine the contribution of each car attribute to its price. Some variables can be coded as a dummy variable, or as a continuous variable. For ...
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### Power Analysis for 1-sample Longitudinal Observational Study

I need to calculate the minimum detectable effect given a known N and desired power. I have a CONTINUOUS EXPOSURE and continuous outcome, each measured twice (baseline + 1 follow-up). If possible, I ...
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### Limit-bound continuous data, how to compare multiple distributions?

We are doing a simple experiment looking at the effect of smell on taste. 200 subjects are given a liquid to taste and asked to rate the favorability of the taste on a scale from 1 to 20. The subjects ...
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### Is there a test suitable for the analysis of my data?

I am trying to compare the performance of pipelines. These pipelines have been sorted into two groups, Insulated and Non-Insulated. I have a total of roughly 60 pipes which are a combination of ...
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### time is a continuous or discrete variables?

I am trying to create a prediction framework of what a customer will buy on a website, so I am confused if time-connection variable (time of the connection of a customer) is a continuous or discrete ...
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### ANOVA with continuous time signal

I have a very large data set of a continuous time signal as measured force(N). I want to do a 4-way ANOVA to compare 12 groups in this data (or compare the signals). My question is, how should I ...
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### Clustering of variables: but they are mixed type, some are numeric, some are categorical

I have a dataset with 15 variables. Some variables are numeric, continuous. Other variables are boolean, dichotomous (true/false). There's also one variable categorical, nominal. ...
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### When is time treated as a discrete variable?

Time is usually treated as a continuous variable but in some cases it is discrete. An example would be with a drug study and measurements are taken at 1, 2 and 3 hours. Am I right to think an ...
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### Is supremum continuous on D[0,1]? Needed for continuous mapping theorem

I am currently in the following situation: I have a sequence of processes which converges weakly to a limit process in D[0,1]. I want to show that the supremum of the processes converges as well to ...
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### What's the variance of the following stochastic integral and is it weakly stationary?

The stochastic integral is defined as $$u_t = \int_{t-1}^t e^{-\kappa(t-s)}\int_0^s e^{-c(s-r)} \, dW(r) \, ds.$$ where $W(t)$ is a standard Brownian motion, $\kappa$ and $c$ are both positive. I ...
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### Interpreting continuous interaction term

I have a question regarding the interpretation of an interaction term in the following model: $$Y=β_0+β_1X+β_2Z+β_3XZ$$ $X$ and $Z$ are continuous and $X$ is negatively related to $Y$, whereas $Z$ ...
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### How to evaluate how well some samples come from some given distributions?

I have a complicated procedure that, given an input $x$, outputs several random samples $S_i(x)$ for $i\in\{1,\dots,k\}$ (each sample consists of $n_i$ points). Each sample $S_i(x)$ follows an unknown ...
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### Mediation analysis with a continuous exposure - Lange et al

It's regarding the method proposed by Lange, Vansteelandt et al. for mediation analysis. In their examples, they explain clearly how to conduct a mediation analysis when the exposure variable is ...
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### Significance of a Dichotomous Variable vs. a Continuous Variable

I ran an analysis using the 2005 healthy eating index (HEI) score as the dependent variable and am a bit confused by my results. The HEI score ranges form 0 to 100, and categorized as bad (<51), ...
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### Applying Cox Proportional Hazards Model on Discontinuous Variable

I am using coxph in Rstudio to apply Cox Proportional hazards model on my data. This model is easy to use on continuous variable ...
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### Measure relationship between continuous variable & unbalanced binary variable

I am trying to select variables for modelling a binary variable (whether a person will repay a loan) using various continuous variables about them - age, income, years of education, etc. I'd like to ...
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### Categorizing Continuous Random Variable in Logistic Regression

I have a Bernoulli response variable and I am going to fit a logistic regression. One of my independent variables is a continuous random variable and I would like to categorize it before fitting the ...
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### How to deal with quasi-continuous features?

I've searched around a bit for strategies to approach the problem I'm facing and haven't come up with much. I'm working with a data set that has many "quasi-continuous" features. That is, the ...
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### How to calculate odds ratio per unit decrease of continuous variable

I have a logistic regression model obtained in R comparing association between two index diagnoses (0 or 1) with Age (continuous) + ...
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### How to set sum contrasts for unbalanced factors

Let's say that I have a model where the response time depends on accuracy (0/1, coded either as categorical or numerical) and another categorical variable (pres: idem/diff), both interacting with the ...
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### 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 ...
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### Marginal likelihood: why integration is used

From wiki: Given a set of independent identically distributed data points $\mathbb{X}=(x_1,\ldots,x_n)$, where $x_i \sim p(x_i|\theta)$ according to some probability distribution parameterized ...
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### Double Hurdle model with continuous DV and two sources of zeros

I want to regress a data set that contains a lot of zero's (~55%) and is determined by a typical 2-stage decision process generating the zeros: Consumer decides to apply for a bank loan or not (0-1) ...
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### Moderated Correlation

I am interested in the moderation of a latent correlation. The model consists of two latent variables with three and four indicators. The latent variables are correlated and influenced by a continuous ...
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### How do I find the percentile p (or quantile q) from a weighted dataset?

Say I have height measurements of Earth's population expressed with a precision of integer centimetres. ...
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### Correlation between binary predictor and numerical response using Linear Regression

I am trying to find correlations between several binary predictors and a continuous response variable. I am not sure what test it is supposed to work for this case, I got confused with all the things ...
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### compute likelihood

How can I compute the likelihood or posterior probability on data when the distribution function is continuous. For example the dist. function is a Gaussian and I have one hundred data points. Now how ...
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### Interpretation of continuous by continuous interaction in binary regression model

I'm performing binary logistic regression in SPSS; y is dichotomous variable; and both Xs are continuous variables. I performed three models and I have troubles interpreting model with both ...
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### Filter Feature Selection approaches for continuous variables?

I've noticed that correlation-based filtering for selecting features in high dimensional data require discretization of continuous variables, like e.g. Fast Correlation-based Filtering or regular CFS. ...
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### Can you explain why this distribution has been suggested for the length of a telephone call

I don't understand what the distribution in e) shows me? I would expect a normal curve about the mean but this is confusing
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### PCA for mixed variables

I have a dataset which contains many variables : continuous and discrete variables. I have a discrete variable adress which can include many value (if for example the customer changes his location, ..)...
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### 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
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### Four standard deviation rules in relation to normality testing

Within our department we were given a set of guidelines for how we might decide whether to proceed with parametric or non-parametric testing (for continuous data). These were drawn up in consultation ...
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### What analysis to use? IV: multiple interdependent levels, DV: continuous variable

My dependent variable is a continuous variable, ranging from 0 to infinity. However, my independent variable has multiple interdependent levels. To illustrate, A person has 6 attributes: A1, A2,... ...
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### Transformations possible when performing a single multivariate ANOVA on a continuous and categorical species database?

I want to study the impact of aquaculture on a hard rocky seafloor community which is naturally low in diversity. 4 replicate images (0.25 m2 each) were taken at fixed distances (0, 20, 40, 80, 120, ...
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### Relationship between categorical & 5 quantitative variables

Im a bit of statistics noob so Im hoping someone here can help me Im doing a research papaer where I've created a virtual market asking the participants which solutions they would like to invest in. ...
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### Using ordinal variable as continuous variable in MLM

In this post, Can I use multiple regression when I have mixed categorical and continuous predictors?, it is stated that you can use an ordinal IV as a continuous IV in a multilevel model. Does anyone ...
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### Using a variable as a continuous predictor in regression even if a middle range of values is missing?

I've been collecting data (various measures) in people with a body mass index (BMI) in the "healthy weight" range (BMI between 18.5 and 25) and the "obese weight" range (BMI over 30) (hence, I've ...
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### How to transform ordinal categorical income into a continuous variable?

I have a large data set including an ordinal categorical income variable and want to transform this variable into a continuous variable. I want to perform a simulation study with the dataset and ...
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### Chi-squared test for continuous variables (averages)

i'm trying to find a suitable statical test for my situation. The best way I can think of describe it is finding a Chi-Squared test for continuous data. Please tell me otherwise. Here is my made up ...