Questions tagged [correlation]

A measure of the degree of association among a pair of variables.

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Fisher r-to-z transformation: comparing correlation coefficient of multiple samples

I am comparing the linearity of a regression model for two independent devices (n=10 each device group). The data is force (newtons) over time (seconds). The regression models show R^2 values of 0.9 ...
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i'm trying to find the correlation between two things but idk how to structure the survey to gather data to do as many statistical tests as possible [closed]

i wanna see if theres a correlation between like how many times a student attends a specific debate tournament held by schools in the country and how many awards they've won. i wanna send it out to ...
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Multiple regression model and correlation between predictors

I am reading the Introduction to Statistical Learning in Python (ISLP) book. I am reading the below paragraph: Now suppose that the multiple regression is correct and newspaper advertising is not ...
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Heteroskedasticity Adjusted Correlation Coefficients

I've been reading Forbes & Rigobon (2002) "No contagion, only interdependence" article, in which they suggest to adjust the correlation coefficients for heteroskedasticity. I can't ...
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What is the best way to calculate confidence interval for spearman correlation by bootstrapping? [closed]

I find important differences for the confidence interval values between the two methods below with bootstrap : First : quantile(Rs, prob=c(0.025, 0.975)) and Second : tanh(atanh(R) ± 1.96 sqrt(n-3)) (...
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How to handle correlated variables before using Recursive Feature Elimination?

I have seen a few Kaggle notebooks that list without reason that RFE works better when removing correlated variables. I struggle to see the reason why so I conducted some of my own research and would ...
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What's the most code efficient way to develop a correlation matrix for all possible factors in a haven() object? [closed]

Let's assume a person is working with a large dataset in R which arises from a survey with a range of possible values, some text, some numeric, and others as factors and that this data has been ...
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Why does feature importance decrease for highly correlated variables?

I am investigating the relationship between correlation between features and its impact on their feature importances using sklearn's DecisionTreeClassifier algorithm. I manipulated the correlation of ...
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Finding similar pairs of students [closed]

Suppose I have a k x k covariance-variance matrix $\Sigma$ of factors (e.g., education background, IQ, height, weight, etc), and a second n x k matrix of factor loadings $F$ for different students (i....
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Partial Correlation and 1 Categorical Control Variable with 3 Categories

I'm trying to calculate the partial correlation between continuous variables $X$ and $Y$ while controlling for $Z$ (a categorical variable with three possible categories). Tutorials and answered ...
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Find correlation from biased observations

I have a set of observations of a variable Z (shown as the colormap) as a function of two other variables A and B. I want to study how Z varies with respect to A, B, and both A and B (eg. if A ...
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How to plot/visualize correlation values from two different methods for comparison?

I am working on a project wherein we are comparing two methods used for modeling gene expression: one method is using elastic net and other is using lasso regression. In one method: we see that ...
Rhea Bedi's user avatar
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Is Fisher transformation appropriate for magnitude squared coherence and phase locking value?

Fisher transformation, or hyperbolic arctangent, is recommend before performing arithmetic on correlation coefficients (e.g., estimating confidence intervals), because it makes their distribution ...
Neuromancer's user avatar
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Estimating the expected autocorrelation x time away given information about how it weakens over time

Let's say I have repeated measurements of some (approximately normally distributed) variable spaced 7 days apart. Is there some way to use the information in these week-to-week correlations to ...
Vilgot Huhn's user avatar
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How to account for confounders in a simple correlation analysis?

Beginner question sorry - I'm a coder and need stats advice. I have a dataset broken down by local area, with columns for the proportion of owners who are French, the proportion of owners who grow ...
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Is it possible to convert a similarity (distance) index to correlation coefficient?

I have two cases that each one has some values on a series of variables (e.g. A, B & C). Is it possible to calculate a distance or similarity index between these two cases and then convert it to a ...
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How does correlation give better model predictability?

Does correlation give better model predictability. In case of using regression models, typically OLS, how does it help with the model predictability and what are its limitations. Any articles or other ...
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What is the best correlation that I can use in order to determine the relationship of these 2 variables?

How can I correlate 2 dichotomous variables? Var1: Passed:1 Failed: 19 Var2: Passed:3 Failed:13 I tried the $\phi$ coefficient $X$: Var1 Var2 $Y$: Passed Failed Everything went well but I realized ...
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What is the difference between the p-value generated when running ANOVA test between categ. and cont. variables compared to the correlation p-value? [closed]

I've got two groups of data one categorical and the other continuous (from 0-100). I converted the categorical into binomial and looked at the spearman's rank correlation coefficients between these ...
Barry R's user avatar
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1 answer
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Sample many correlated random matrices all with the same pairwise correlation coefficient

I am looking to generate $K$ different correlated random matrices, of which the elements all have the same pairwise correlation coefficient. That is, let $A_1, A_2, \ldots, A_K$ be $N \times N$ random ...
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Everyday life example of spurious cause and effect relation

I'm stuck on the following issue. I want to find simple examples from everyday life where it's clear that a categorical and a quantitative variable are not connected by a cause-and-effect relationship....
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How to draw samples from two correlated Negative Binomial variables?

Data and problem description: my data is the number of corner kicks of home team, away team, total corner kicks and corner kicks difference. Below is code for data and the plots (assuming the number ...
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How to assess whether two variable are independently correlated?

I have a data set with three variables: A, B, and C. There are correlations between A and B, B and C, and A and C. I'm trying to figure out whether the correlation of A and C is purely a product of ...
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Determining values for Default Correlation between two companies

I'm a second year undergrad university statistics student working on a real life project for IDB, a bank in Latin America. However the project is really above my level, and I could do with some help. ...
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Approximation for a correlation matrix

I have a cross-correlation matrix of some parameter for each time period. E.g. expected economy growth for each months in the future, i.e. growth for Apr 2014, May 2014, ...., Dec 2018, and ...
guygsakjdfbnasdbff's user avatar
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Input-Output Correlations using PCA

I want to understand the correlation between a set of $\color{red}{\textrm{inputs}}$ and a set of $\color{blue}{\textrm{outputs}}$ deriving from numerical simulations, and possibly reduce dimensions ...
lukewarn's user avatar
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Which correlation analysis method should be prioritized when different methods yield completely different rankings?

I've been working with an industry-related dataset where I need to analyze the correlation between a specific output (y) and several inputs (x1, x2, x3, etc.). During my search, I came across various ...
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2 votes
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Using FIML (Full Information Maximum Likelihood) for simple correlation test on data with missings?

I have a dataset with missing values. Since my main hypothesis is just a simple regression, my adviser told me to use FIML regression. So I used lavaan package: ...
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Mixed model in lme4 package is singular

I am running this model: ...
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311 views

Cronbach alpha - descriptive statistics

I researched thinking styles based on Sternberg's Investment Theory. I used a TSI questionnaire that measures preferences in thinking styles. The problem is that I got low scores of Cronbach's alpha ...
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Correlation of event occurrence in multiple sectors

I have the following problem to analyze: I divided an area into several sectors (i.e.: S1,S2,S3,…,Sn) and there is an event that can happen in one or more sectors at the same time. I considered a ...
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Why is the correlation coefficient of these subsections of this dataset indicating a much weaker correlation than the whole dataset?

I have a dataset which includes household income against expenditure. The correlation coefficient of the dataset is 0.7064 which indicates a strong positive correlation. Here's a graph for it: Now I ...
Marmaduke Bonthrop Shelmerdine's user avatar
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Assessing surrogacy for 2 treatment effects

I'm interested in analyzing whether an intervention's effect on an outcome, X, qualifies as a surrogate for its effect on another outcome, Y. By the end of the analysis, I would like to have: A) An ...
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Do you change the mean / standard deviation when calculating the unbiased normalised autocorrelation function?

I am trying to calculate the unbiased normalised autocorrelation function. I think this field is a little complicated as different sources appear to use different nomenclature to describe the same ...
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Measuring features effect and importance in Partial Least Square (PLS) regression

Context: it is possible to assess features importance and effect for a model using model-independent scoring techniques such as Partial Dependence (PD) profile, Acculumated Local Effect (ALE) profile, ...
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How to correlate several binary (binominal) variables with each other?

I have a dataset that describes the answers of students to 7 questions (correct/wrong). So: Question1 Question2 ... Question7 student#1 correct correct wrong student#2 wrong correct correct ...
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Imaginary numbers in PCA output

Using PCA manually on correlation matrix, I'm getting imaginary numbers in both eigenvalues and eigenvectors. Is this expected behavior? I understand that when interpreting a matrix as a linear ...
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Finding a modern derivation of the biserial correlation

Jacobs (2017) states a formula for the biserial correlation coefficient, citing Pearson's original (1909) paper. I find that old paper hard to read. Does anyone know of a modern derivation of the ...
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Using Cramer's V to find which variable has the strongest correlation

Apologies in advance if this has been asked before; I'm a stats amateur and wasn't having much luck with my searches. I'm currently analyzing product data, and I'm trying to find which variables (all ...
Ash M's user avatar
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Correlations among rankings

In my study, participants ranked their preferences for several choices. Because moving one choice up necessarily means moving one or more choices down, nearly all correlations (Pearson's r) are ...
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Dimensionality Reduction while Preserving Statistical and Correlational Features [duplicate]

I am working with a dataset comprising $k$ matrices, each representing different asset classes such as Stocks, Bonds, Linkers. Each matrix is of size $m \times n$, with $m$ being 10,000 simulations of ...
KingDingeling's user avatar
5 votes
1 answer
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"Famous" set of correlation plots used for teaching

I am familiar with Anscombe's quartet I am now looking for a different set of plots. From what I remember, these all had correlations of zero, and there was a question here on CV, and I think it was ...
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Can correlation analysis be applied on data of control vs treatment study?

This might be a weird question, but I have been asking myself the question for quite some days so I hope that someone can help me out: I have conducted an in vitro experiment where cells were treated ...
Tom H's user avatar
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Methods for Dimensionality Reduction while Preserving Statistical and Correlational Features [closed]

I am working with a dataset comprising $k$ matrices, each representing different asset classes such as Stocks, Bonds, Linkers. Each matrix is of size $m \times n$, with $m$ being 10,000 simulations of ...
KingDingeling's user avatar
2 votes
1 answer
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Generate samples from multivariate correlated data which have non-parametric cumulative distribution functions

I have 40 samples that contain information about 6 variables (hence a 40x6 data matrix). Each variable (column) has a cumulative distribution function (marginal distribution) based on the 40 values, ...
1 vote
1 answer
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How to find relationship between a categorical nominal variable and numerical variable? [closed]

I am interested in finding the relationship between a nominal categorical variable and a numerical variable. We can't use scatter diagrams, or measurements of correlations for finding such ...
Main's user avatar
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Choosing Predictors in Multiple Regression

I am planning regression analyses and present this (hypothetical) scenario to communicate my query. I am interested in the effect of 2 different measures ('IQ' and 'SPQ') on dependent variable '...
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Best practices for correlating clinical variables with gene expression data

I am working on gene expression data from humans and disease models, where I want to correlate important measures of disease severity, i.e. clinical measurements, with the gene expression. I am trying ...
A Marstrand's user avatar
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How do I transform this regression?

I am researching bladderwrack and whether they can adjust their amount of bladders (small inflated bags of air that develop on their skin) depending on how wave-exposed the surroundings are. Hence I'...
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Sampling inquiry for thesis [closed]

I have a mixed-method thesis ongoing and I plan collecting data on my own college (namely college X), specifically from students and faculty members on my department. Evidently, that would be ...
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