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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How to analyze dataset for an ecological study? [duplicate]

My independent variable is health care system (continuous and non normally distributed) and dependent variable are health outcomes(continuous) . This data is available for 40 cities. How should I ...
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How to analyze small dataset? [closed]

I have a small dataset with continues variables , dependent variable is normally distributed and linearly associated with the independent variable. I tried doing linear regression but the model doesn'...
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19 views

How to analyze country specific data with 40 data points?

I have country specific aggregated data with 40 data points. My independent variable is the availability of health care facilities and dependent variable is infant mortality rate. I tried using linear ...
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scipy norm.pdf return probability of a particular outcome [duplicate]

The Probability of a particular outcome is always zero, but Scipy's norm.pdf() function returns the probability value of a particular event. For example onlinestatbook.com/2/calculators/normal_dist....
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Some clarifications on guidelines for preparing frequency distribution of grouped data

Some of the guidelines given for preparing Frequency distribution for grouped data or "Grouped Frequency Distribution" are given below. I have some doubts regarding the same All classes or ...
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Which IRT model is recommended to capture manifest continuous indicators (items)?

The test under investigation comprises of continuous items, whose response space is not limited to a special interval (such as [0;1]). Instead, my items are developed for measuring the execution speed ...
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24 views

Performing Naive Bayes Calculations with Continuous Features

I am working on this homework problem and am not sure how to handle continuous features in a Naive Bayes classifier. I know the outputs for the categorical variables are simple to compute, for example:...
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What does it mean to train a Naive Bayes classifier for categorical features?

I know that Naive Bayes classifiers can be trained for both categorical and continuous (using a Gaussian distribution) features. I am less certain of how these two classifiers would differ. What does ...
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Linear Mixed Effect Model: Control for Continuous Variable that Changes with Condition

This is a neuroimaging study. I have a repeated measures study, where each subject has been scanned under two conditions (Movie1 and Movie2) (same day). I have measured how much they moved during the ...
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Type of Data resulting from Aggression Tests [duplicate]

I conducted a series of behavioural tests on termites, where I observed individuals and counted intercolonial interactions. Interactions were weighted differently, according to how well they indicate ...
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2answers
60 views

What statistics test to use to compare multiple groups with different sample sizes

I'm running a test where I need to compare four groups on different dependent variables. Two of them are categorical and I'll a use Chi-squared test for the head-count while one y is a continuous ...
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1answer
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Correlation between Migraine Events and Barometric Pressure [closed]

I have historic air pressure line graphs and I have superimposed the dates on which I have suffered migraine attacks. I can see that my migraines are most likely to occur around 3 days after a sharp ...
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1answer
26 views

Correlation between two constant variables using the different approaches [duplicate]

Let's say we have a vector X = (1, 1, 1) and Y = c(2, 2, 2). I want to calculate correlation between those. Taking Pearson ...
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Can I obtain a multivariate gaussian likelihood using an Ornstein - Uhlenbeck process?

I am interested in calculating the likelihood of a gaussian process, assuming that we have a continuous record of measurements in an interval, e.g. [0, 1]. In this paper, equation 14 gives an ...
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How is this connection between Beta and Binomial possible?

I'm learning stats, and I've reasoned about this for many days and I'm losing sleep over it. Say I have a binomial distribution B(k; n, p) simulating a hypothesis <...
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Why the sum of two absolutely-continuous random variables isn't necessarily absolutely continuous?

Why "a sum of two absolutely-continuous random variables does not need to be absolutely continuous"? See problem 6.4 on page 6 in https://web.ma.utexas.edu/users/gordanz/notes/...
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Transforming data with a range of values

What is the best way to compute descriptive statistics from a wage_range variable collected as follows and use it for OLS purposes or should this variable be completely ignored from empirical analyses:...
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Converting continuous predictor to category e.g. Age [duplicate]

I notice that on many examples one is keen to convert Age to a categorical age range. I am wondering if that is always necessary. The famous golf play decision tree example has ranges for temperatures ...
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Excel NORM.DIST() calculation for a specific value of x (CUMULATIVE = FALSE)? [duplicate]

We know that the value of PDF at a specific time (X = x) is 0 due to the nature of a distribution of a continuous variable. However, I noticed that when I plug in some test numbers in NORM.DIST() in ...
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1answer
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How should one understand Bayes theorem with probability distributions?

I'm learning about VAEs, and need to go this deep to understand them. However, the question is for Bayes theorem with probability distributions. I learnt about Bayes theorem from this video. Excellent ...
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2answers
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If $X$ is a continuous random variable with support $A$, does this imply that the cdf of $X$ is strictly increasing on $A$?

If $X$ is a continuous random variable with support $A$, does this imply that the cdf of $X$ is strictly increasing on $A$? My guess is yes. But just in case, let me know if you can think of any ...
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Modeling covariates in multiple regression

My aim is to find the association between intake of chocolate (continuous predictor) and blood pressure (continuous outcome) in a multiple linear regression. I have to include many covariates in order ...
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Doubt on regression analysis interpretation

I have a dataset made of more than 10K observations. For each of them I know the value of a continuous variable (C1), and the value of three nominal variables: N1, which can take three different ...
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129 views

How to interpret crossover-interaction between continuous and categorical variable?

I am stuck with the interpretation of my model results. In the beginning I have tested my independent variables for correlation with Theil's U and left out correlated ones to avoid multicollinearity. ...
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Do I have to apply the same kind of transformation and scaling to all data? [duplicate]

I'm new to machine learning and currently learning it, and I do not quite understand the topic of continuous data transformations for machine learning. If I have 6 pandas columns of continuous data, ...
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What analysis should I use for longitudinal (observational) data with continuous IV and DV?

I collected data from the same participants twice over two weeks (time 1 and 2 are two weeks apart). Between time 1 and time 2 there was a significant event, which we hypothesized, would've changed ...
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How to model zero-inflated continous (from negative to positive) data

We have a dataset of around 20k observations. The dependent variable is the change (i.e. delta) on the amount of a common resource (e.g. land) of individual households in a year, so: It has negative ...
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Probability of intersection involving a continuum

I'm trying to derive pascal's rule of succession that I saw on a 3b1b video in a rigorous-like way(i don't have a solid background in measure theory so I can't pretend to be rigorous). let $ ω=[0,1] × ...
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56 views

Likelihood of Gaussian Process for continuous data

I need to calculate the likelihood $L(\theta)$ of the Gaussian process: $ y(t) \sim GP(m(t), K((t,t')|\theta)) $ where $m(t)$ is the mean function (this will be zero for my purposes) and $K((t,t')|\...
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In real-life applications, which continuous distributions have NON-CONVERGENT expectations that require Lebesgue integration?

When computing expected values, Riemann integration works for only random variables with bounded support sets. For distributions with unbounded support sets, we can use improper Riemann integrals for &...
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Variable data measured discretely with poor resolution

Is there an appropriate method for estimating variation when variable data is measured discretely where the resolution is poor. Here's an example: You are looking at how long it takes for a solid to ...
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1answer
30 views

How to decide whether to use regression or classification model?

I just started machine learning , and I was confused about which model to use, regression or classification , when we have a target variable like age or a variable like movie rating , which may have ...
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97 views

Latent Profile Analysis in R with continuous and categorical variables

I am trying to do an LPA with categorical and continuous variables. The tidyLPA package is amazing for continuous variables but models don't seem to converge with categorical variables, and the ...
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24 views

Represent Integer Categorical feature as both Numeric and Categorical

I'm dealing with tabular datasets where it's really hard to tell if the integer column is Numeric or Categorical. My main consideration is the accuracy of the model that I am building (no deep ...
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Analysis of One Binary Variable and Continuous Variables - Ecological Data

I have a dataset that I am trying to analyse, it consists of: A binary variable which indicates a tree species (0 = deciduous 1 = evergreen) with 100 measurements each. N which is leaf nitrogen ...
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150 views

How to compute the median of a continuous distribution?

I don't have a solid background in statistics so the concept of probability density functions in the statistics course I'm taking is new to me. I need to derive the median of a continuous distribution ...
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1answer
28 views

In practice, how to discretize continuous regressor with minimal impact on coefficient (or minimal information loss)?

Suppose I have some continuous data that looks like this (this is a mini example, not my real data): ...
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1answer
24 views

Are zero inflated models appropriate if the predictor/x variable is the one that is zero-inflated?

As the title suggests. I was under the impression that zero-inflated models are generally used when zero values are over-represented among the response/y variables, but now I am dealing with a ...
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22 views

Multivariate Regression: Both Continuous and Categorical Predictor Variables

I am involved in a meta-analysis assessing the role of multiple baseline characteristics (e.g. age, BMI, symptoms and signs) in a given disease. One element of our analysis includes a multivariate ...
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What's the good way to find outliers in the continuous physical process measurements time-series? (picture attached) [duplicate]

What's the best way to find outliers in the time-series like the one attached? Just using the knowledge that it is a measurement of a continuous physical process. The data is quite short (200-500 ...
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1answer
30 views

Can we normalize both continuous and discrete numerical values

I have a sensor dataset with 16 features as numerical values (12 are continuous and 4 are discrete). I am using LSTM model to fit the data and do some classification. As both continuous and discrete ...
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1answer
166 views

How to estimate the optimal cutpoint for a binary outcome in python?

I have a dataset of diabetic patients which has been used to train an xgboost model in several outcomes such as stroke, amputation, and more. Originally we used the continuous numeric variables as-is, ...
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1answer
65 views

What's the best way to find outliers in the time-series, encountering that it is a real-world mechanical process (process continuity)?

What's the best way to find outliers in the time-series, encountering continuity? I attached two time-series that I'm interested to filter. One is less noisy, and one is a bit noisier. I'm mostly ...
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23 views

Interpreting logistic mixed model estimates of a model with continuous and categorical predictors

Newbie here. Sorry in advance if I express poorly as I don't completely master yet the vocabulary of statistics! I am performing a logisctic mixed model - with glmer - which presents as follows: CE ~ ...
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14 views

creating a continuous variable from ordinal variables

Could I simply sum up ordinal variables (some 4-,some 7-scale) to create a continuous dummy variable, and include it in a regression model? E.g. ...
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1answer
63 views

Stratify Cox Proportional Hazard Model on continuous variable

I have a question regarding Cox proportional hazard models. I've been working with data with some time-varying variables and some that are fixed over time. In total 79 units are surveyed giving around ...
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1answer
44 views

Years as continuous variable [duplicate]

Can I use "years" as a continuous variable ("years" as calendar years from 1984 to 2014) to see if NDVI (normalized difference vegetation index), of the same area at the same time (...
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1answer
61 views

Positive or negatively bounded CDFs [closed]

If $X\in\mathbb{R}^n$ is a continuous random variable whose cumulative distribution function is ordinarily $$F_X(x) = \int_{-\infty}^{\infty} f_X(x) dx $$ what is the meaning of $$F_X(x) = \int_{0}^{\...
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17 views

How to conduct meta-regression with a continuous variable measured on different scales across studies?

I am conducting a meta-analysis on the efficacy of a specific type of psychotherapy for children and plan to use meta-regression to identify moderators. The predictor I am interested in is parent ...
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2answers
98 views

Sample size calculation for linear regression model with random intercept

I am trying to calculate the sample size for a mixed linear regression model. The dependent variable is continuous and the model includes 2 further continuous variables. The random intercept is based ...

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