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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Why variable representation plays a role in prediction?

I am working on binary classification using a random forest, where the data have 977 records and 6 columns. The class ratio is 77:23. I have two derived input variables. One variable is called ...
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R Mediation with continuous predictor and binary logistic regression models

I am running a mediation model using the r mediation package, but I am not getting the correct output for my variable types. I have a continuous predictor, but the output is treating my predictor as a ...
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How to consider categorial ordinal variable?

First, I would like to apologize because I'm a beginner in statistics and I'm surely confused on some points. I would like to explain a continuous quantitative variable, which is a species activity, ...
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Salary of a group of people is continuous or discrete

I have salary data of 3000 employees ranging from 3000 - 10000 dollars. Based on my understanding:(https://mathbitsnotebook.com/Algebra1/FunctionGraphs/FNGContinuousDiscrete.html) Continuous data is ...
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Trying to Understand my Data: New to Statistics

I’m new to statistics and I’m a bit overwhelmed by all of the methods that I’ve been reading about. I’m finding that my biggest hurdle is understanding how my data would fit into different models. I ...
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How can $N(x|\mu, \sigma^2)$ not be 0?

How can $N(x|\mu,\sigma^2)$ not be 0? Because a Gaussian distribution is continuous and therefore there are an infinite number of values that x can occupy in the Gaussian distribution therefore the ...
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Distance is Quantitative continuous, Quantitative continuous on a ratio scale or Quantitative continuous in scale of intervals?

I have sample data and I have one variable which records distance from resident to place of work. I have to chose that this variable is actually of what type. It is Quantitative continuous for sure. ...
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Is feature scaling needed for dataset containing non-categorical and categorical independent variables?

I have a dataset containing 800+ label encoded (2-level as 0 or 1) categorical features and 4 non-categorical numerical features. The dependent variable is a non-categorical numerical value. Should I ...
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Interpreting a factor variable as numeric when quantity is clear and obviously continutous?

I'm looking at a data set from a famous paper by Box & Cox (An Analysis of Transformations) that reports the results of an experiment with yarn machines. It involved 3 factors with 3 levels each: ...
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Continuity of a multivariate CDF at a point

I want to show that if $(X_1,X_2,\dots,X_n)$ is an $n$-variate random variable, then its CDF is continuous at a point $\vec a$ iff $$P\left(\bigcup_{k=1}^n\{X_k= a_k, X_j\le a_j\:\forall\:j\ne k\}\...
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If multiple variables add up to 1, are they independent of each other?

I am trying to test for association between continuous fractions of cell types in a sample (e.g. immune cells, cancer cells, fibroblasts...) and tumour grade (categorical/binary/ordinal, grade 1 or 2)....
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Understanding continuous variable entropy

I am struggling to understand continuous variable entropies and mutual informations for 2 or more variables. Consider 2D normal distribution $\rho(x,y)$ defined as follows $$X\sim\mathcal{N}(0, \...
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What hypothesis testing to use for continuous to categorical variables?

For example, I'd like to know if a person's age (a continuous variable) is related to whether the person drinks (a categorical/binary variable of Y or N). What method should I use to know If there's ...
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Are Hidden Markov Models the right tool for signal segmentation task?

I have a particular problem, and I would like to know if using a HMM is the correct tool for it. Apologies for the poor wording of the problem, HMMs are definitely not my specialty. I have the ...
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Visualizing multivariate multiple regression of continuous data in R

I have created a multivariate multiple regression model with 3 dependent and 3 independent variables in R, and would like to generate meaningful visualizations. All variables are continuous. When ...
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categorical and continuous fixed effects in a linear mixed model

I heard that you can not combine continuous and categorical predictors in a linear mixed model. Is that true? Also, I was told to use continuous variables as random effects. Does that make sense? As ...
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Repeated measurements and sample size calculation for medical device

I’m trying to work out a sample size for a new device which measures a variable continuously over 1 hour in a participant (measurement 1). This variable will be compared with another measurement (2) ...
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How to report and interpret a parameter of a SEM model with categorical and continuous variables

I have conducted a SEM model in MPlus where X and Y are categorical and M is continuous. So the path from X to Y are log odds, the path from X to M are betas, and the path from M to Y are log odds. I ...
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What is the right model for regression analysis with categorical, numerical and binary data?

I am currently stuck in choosing the right approach to investigate my dataset with Python (seeking for correlations between DV and IVs). Below I am trying to summarize everything that may be necessary ...
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How to compare means

I have 2 variables in my data. One variable is continuous and it is the dependent variable (grammaticality ratings). The second variable is categorical and has 6 levels (6 grammatical structures). I ...
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Interpretation of two dummies interacted with one continuous variable

I am currently looking at the following equation using Stata and unsure of how to interpret the interaction terms when there are three variables interacted together (2 binary variables and one ...
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Predicting a continuous outcome from trichotomic variables

This question is somewhat related (but no identical) to this previous topic. I would like to predict a positive continous variable $Y$ (namely, the age in years) from about 40 trichotomic variables. ...
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Is the use of cutoffs for dichotomisation of biomarkers really that bad?

Tissue microarrays are commonly used to assess potential prognostic biomarkers. For decades now, many authors (I would even say the majority) feel the need to categorise their continuous predictors, ...
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How to define Unit-specific quantity of the effect of a continuous variable on another continuous one?

Recently Lundberg, 2021 [1] emphasized the necessity to define a unit-specific quantity, target population, and causal diagram, to clarify the theoretical and empirical estimands of any quantitative ...
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What are the best algorithms to predict a continuous target where I only have binary attributes? [closed]

Hello, I am new to machine learning and have a project where the dataset consists of binary attributes and the target("Pawpularity") has a continuous value. I was wondering if you could ...
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Repercussions of misclassifying variable type during correlation determination?

I have multiple variables like as below a) Product Ids (input - nominal/ordinal) # This column has repeated values (though the ids are specific for a product) b) Product Type (input - nominal) c) ...
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Is z-transforming continuous variables always necessary?

I fitted a LMM with two continuous variables (actually they are more like discrete variables,varying from 0-7)and a categorical variable. The summary function showed that the two continuous variables ...
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categorical IVs, continuous moderator and DV - statistical test

I'm planning an experimental research. My research question is when do my treatments could be effective in influencing intention. Below are variables to be set. treatments / scenarios / IVs: 3 ...
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How should i treat this data, as a covariate or as a factor?

In my research group, I'm in charge of the statistical analysis of the data generated by the team, but I am fairly new to all of these statistics. So, I have this ambient temperature data (which on ...
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How to model the joint distribution of continuous and discrete features (and estimate the model)?

Suppose a typical house in the market has 3 features $X_1$, $X_2$, $X_3$. $X_1$ is the square footage of the apartments interior living space, $X_2$ is the square footage of the land space and $X_3$ ...
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How to treat a continuous variable in logistic regression that has only a few levels? Ordinal vs continuous

I'm building a logistic regression model, predicting recidivism which is the act of committing a crime after one has been released from prison for a prior criminal deed. One of the variables in the ...
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Binned continuous x axis and stacked probability bars on y axis - does this plot have a name?

After reading a question about binned continuous x axis and stacked probability bars on y axis I am wondering whether this plot has a name. Here is an example: What this plot shows: We see how the ...
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Suppose $X$ follows normal and $Y$ follows Bernoulli, wrt which measure does $(X,Y)=(-0.005,1)$ have a measure zero?

Suppose $X$ follows standard normal distribution and $Y\in\{0,1\}$ follows Bernoulli(0.5),i.e., $Pr(Y=1)=0.5$. Intuitively, I know the point or event $(X,Y)=(-0.005,1)$ has a measure of zero. But I ...
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One continuous variable and one categorical variable (with four categories)

I have a dataset and want to see whether participants’ happiness ratings were affected by the season they were interviewed in? How do I do that in R since my categorical variable has four levels?
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Getting binary class from continuous values of neural network output [duplicate]

I have a custom neural network that I wrote from scratch and it does lot of mathematical computations and the output is a continuous value. I want to get the binary class output from these continuous ...
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Number of bins for discretization

How do I decide on the right number of bins to discretize my continuous data? Are there are tests/techniques to do the same? Could someone give me some idea into existing approaches?
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Handling null continuous values in Logistic Regression with inverse values

I've got a data set of prisoners, where the measured variable is the probability of a recurring act of crime, which is counted as having occurred when a former convict is interrogated as a suspect in ...
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Estimating mutual information with gaussian kde between two continuous variables in python

I am trying to write a python code to estimate the mutual information between two continuous variables in python, using a gaussian kde to estimate the probability distributions. Checking it with ...
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Binomial GLM with Logit Link on Continuous Data given Frequency Weights [duplicate]

I'm wondering what R is doing in the background when given rate/proportion data and frequency weights. The Binomial GLM should only fit {0,1} data but the results still seem fairly accurate. Does it ...
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Should I convert my numeric arbitrary values with ordinal ones?

I'm testing the scores of a test against those of another, related test. In the X axis, I have the sum of 15 questions, 1 point each. In the Y axis, I have the sum of 4 questions, also 1 point each. I ...
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mean center interaction term

I'm using multiple linear regression to measure both the main effects of SES (income, household size, education level) on a kindness scale, adding an interaction between income (rating between 1-7 ...
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What method for analysis of pooled data (continuous variable) [closed]

I sought to perform meta analysis of continuous variables I have extracted mean and SD from multiple studies for a variable What is the statistical method to compute a "global" mean + SD ...
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Variance of one sided truncation (of upper tail)

I have a random variable $x$ with $E(x) = \mu$ and PDF $f(x)$ and CDF of $F(x)$. I was thinking about the variance-version of $E \{ x | x < \bar{x} \} = \frac{1}{F(\bar{x})} \int_{-\infty}^{\bar{x}}...
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How to tell whether a variable should be treated as continuous or categorical?

Suppose I used a multiple linear regression to model the association between cognitive score (Y) and sleep quality (X) along with other variables (gender, age etc.). ...
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Is it possible to transform probability distribution? [duplicate]

Let's say I have a real dataset. One of the "Features" let call it X1 follows Weibull distribution.Can I change X1 distribution from Weibull to exponential or to any continuous distribution ...
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Find expected value and variance of a function of a random variable given its expected value and variance

I am now being introduced to rigorous statistics and doing some self-learning. A question recently came to mind: Suppose I have a continuous random variable $X$ and I know $E(X)$ (expected value) and $...
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Why do discretised predictors have lower statistical power than continuous predictors?

In designing an analysis, I'd like to decide between using discretised variables versus using the original, continuous variable (the reason being that in this particular case, collecting discretised ...
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Can I pool studies in a meta analysis with binary and continuous outcomes? [duplicate]

I'm currently completing a meta-analysis (in r using the meta/metafor package) looking at predictors of treatment response in patients suffering from a particualr mental disorder (psychosis). Some ...
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PR estimation of a cross sectional study with a continuous variable possibly by Cox proportional hazard regression

I have a table of a simple cross sectional data: ...
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Infinite mutual information for continuous multidimensional random variables

I am struggling with understanding the notion of the infinity of the mutual information. Say, one has an multidimensional continuous Gaussian variable $(X_1, X_2...X_d)$. Why would the mutual ...
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