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Questions tagged [correlation]

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

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Multi-year and multi-location correlation or regression?

I have fire activity data (i.e. number of fires) and a series of factors (e.g. precipitation, tree cover loss, distance to nearest forest, etc...) that can potentially explain it. I have all this data ...
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Relation between independence and correlation of uniform random variables

My question is fairly simple: let $X$ and $Y$ be two uncorrelated uniform random variables on $[-1,1]$. Are they independent? I was under the impression that two random, uncorrelated variables are ...
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If a study indicates no correlation between two variables, does it also indicate a lack of casual relationship? [duplicate]

Of course, correlation does not equal causation. But I am having trouble understanding if there is no correlation between two variables, would this indicate a lack of casual relationship between them ...
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Is it good practice to use Linear Least-Squares with SMA?

I have time-series (daily) data and I want to understand the general trend. My current approach is: Calculate the 7-day simple moving average. Add a line of best fit (linear least squares ...
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What is the difference between sensitivity analysis and correlation analysis?

How do you compare them with each other in the statistical context? I have a set of inputs and outputs for which I build a random forest model. Can I use the model to perform sensitivity analysis ...
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Generate value of variables for given correlation coefficient

I would like to generate test data for script used for correlation analysis between quite long variables. Is it possible for a given length of vectors, to generate in relatively simple way ...
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Correlation between previous year growth and monthly climate variable

I want to calculate Pearsons correlation coeff. between growth variable (tree-ring measurements) and monthly climate variable (e.g. monthly average temperatures) for a period of 100 years. In that ...
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1answer
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Adjusted Mean of Variable given Single Covariate with Weak/Moderate Relationship

Say I have two variables X and Y, each a data set with corresponding data points 1 through n. These two variables have some casual, small but significant relationship (low r value). Then I am unsure ...
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Pearson and Spearman correlation on absolute values with its change over time

I am trying to correlate the absolute value of one variable with its change over time. I have 4 time points in my data when the same subject is re-assess: baseline, TP1, TP2 and TP3. It seems that ...
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is it scientifically correct to label data by model built using golden data?

I am trying to find a labeled dataset for users profiles pictures with their personality traits scores. Unfortunately, I did not find any and therefore, I decided to crawl twitter for public users ...
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Controlling for spatial confounding in point-referenced data

I have a point-referenced data set with 2 binary outcomes. The data shows a strong correlation between these binary attributes - however, the geographic clustering is also qualitatively clear. I would ...
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Weird result on my Lm function in R [closed]

I have plotted a scatter plot on R with the line of best fit. However when i use the lm function for my data the values do not correspond with the line of best fit on the graph. For example as you can ...
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Why use a mantel test instead of calculating pairwise differences and then fit linear regression model?

I am trying to determine whether the similarity in species composition between 100 sample sites is related to differences in terms of precipitation between those same sites. Most published studies I ...
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2answers
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Linear regression vs. Pearson's [duplicate]

I understand that linear regression is finding the "best fitting line" and Pearson's r is measuring correlation between two variables, but I can't visualize this difference. I had a project where I ...
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Data simulation in R for longitudinal data [on hold]

I want to design a study for longitudinal antibody titre that will eventually allow me to estimate geometric mean and limits of detection. I want to simulate data that i can use it for that in R. ...
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How would one compare a correlation with a downsampled one?

A little background: I was repeating an experiment done 15 years ago. Back then their measurement device was slower and aggregated 5 minutes of data. Now I can directly process the data and get ...
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Using the appropriate method for measuring the similarity of 1-D discrete time series data

I have a data of a 1-D time series data (more than 4000 points), they have fixed spacing, sample at fixed frequency. My task is to 'extract' the part in this data that match/look similar to my input ...
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A tool to find cross-correlations between large set of metrics

Given a table with hundreds of records each with the same number of factors (about 1000), I would like to be able to produce a report that shows which factors self-correlate in pairwise fashion or in ...
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Variance of residuals and population variance

I am just a bit confused about a statement in Murray (2006), Econometrics: A modern introduction: Consider a random variable $Y_i$ with mean $\mu$ and variance $\sigma^2$. If we have an intercept-...
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Correlation between neighboring timesteps in EEG data

Problem In a class I am taking now, the professor claimed that there is strong correlation between EEG voltage values in neighboring timesteps and subsampling data (say, sample data every two ...
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1answer
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Explaining the difference between Pearson correlation and distance correlation

This question and its answer might highlight my naivete regarding Brownian/distance correlation. I'm using the difference between a matrix of distance correlations, as calculated by ...
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1answer
28 views

Create composite variables using items with different scales- dealing with multicollinearity

I have IV's that are highly correlated with one another. The first set of correlated IV's, I combined them by adding the score and dividing by 2 to create a composite score. This was simple because ...
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does stepwise regression only work when there are a few explanatory variables with a significant correlation with the dependent variable?

I understand that stepwise regression is computationally intensive in general but is it only "suitable" in cases where you can ignore several variables from the model due to statistical insignificance,...
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Compare samples with noisy data and maximums

Summary: I collected psychophysical data (i.e. yes/no responses to physical stimuli) testing the ability to feel a touch stimuli. I used a Bayesian algorithm to select the stimuli (30 trials per ...
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How to show sample correlation is sample covariance for standardized values?

Given a matrix $X$ and the resulting sample correlation matrix $R$, consider the standardized observations: $$\frac{(x_{jk} - \bar x)} {\sqrt{S_{kk}}} \quad k=1,2,...,p \quad j=1,2,...,n$$ Show that ...
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How to separate subjects into a handful of clusters depending on multidimensional correlations?

I am doing a research project on tobacco toxicity and have measured several biologic and physiologic parameters in the same patients (>15 parameters). Subjects have been exposed to 3 types of ...
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1answer
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What is the formula for calculation of `R_ij` in `numpy.corrcoef(x, y, rowvar = False)`?

The manual does not provide the formula if we pass x and y. I do not understand the matrix I get. Here is my code: ...
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1answer
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Least squares regression coefficient with minimal information

If I only have a correlation matrix of 4 variables and the sample size, is it possible to predict 1 variables from the other 3 while using information about sample size? I’m trying to use lm but my ...
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Events with two sets of weights - correlated weighted Poisson distributions?

Let's say I have a set of $N$ events with weights $w_i$. $w_i$ follow some distribution, the same for all $i$, that I either know or can approximate. $w_i$ and $w_j$ are uncorrelated for $i\ne j$. ...
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Multiple regression including uncorrelated independent variables

I have two independent variables, one (variable-1) has a significant correlation with the dependent variable and the other (variable-2) does not. I want to first do multi-regression analysis (spss ...
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Comparing regression slopes obtained in the same group at different times

I have a group of participants. I obtain two biological measures at baseline and then take the same two measures again after a period of time has elapse. I wish to determine if the relationship ...
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Can someone help me understand this plot?

I am struggling to understand the outcome of DCC GARCH correlations in this plot. I don't understand how the y-axis points are the same even though the correlations look like they are moving over time?...
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How to find influance on correlation of single value

I need to find possible errors or outliers in my data sets. I want to find most affecting values of my pearson correlation. For example let say we got two data sets for X and Y: ...
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1answer
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Coefficient of multiple correlation for multiple linear regression with degree > 2 and interaction terms

I want to calculate the Coefficient of Multiple Correlation $R^2$ for a multiple linear regression with polynomial features of degree >= 2 (with interaction terms). Let's say I want to obtain the ...
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Causality analysis

I'm trying to find causes for my lack of sleep through data. I'm hoping to be able to input information throughout the day like "drank coffee", "Exercised", "meditation","what I ate for dinner" ... ...
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1answer
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Analysing count data for biology

I have twenty observations of three dependent variables and of sixteen independent variables. The dependent variables are: 1) number of species, 2) number of individuals, and 3) index of Shannon. The ...
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What should I use to analyse the relationship between independent and dependent variable, correlation or regression?

i'm anuradha I am going to test the relationship between inventory management and financial performance with four independent variables and two dependent variables. Inventory turnover, inventory to ...
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How to deal with correlated regressors in a multiple regression model?

i currently try to estimate the effect of different task parameters (IV) on neuronal activation (DV). Some predictors in my design matrix(trials x features) are moderately correlated (r~=.3) and I ...
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Shouldn't the absolute correlation between 2 observations be 1, regardless of the number of features they have?

I was going through the "An introduction to statistical learning in R" book and came across this part The passage seems to suggest that 2 observations will not necessarily have a correlation of 1 ...
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How to measure the association/correlation between two unordered category distributions

I have seen the questions like Correlations with unordered categorical variables , but I cannot implement the chi-square test since I don't have a chi-square table representing joint distribution. ...
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Plotting correlation coefficient against regression coefficient

I have samples taken in different places with yearly data for temperature and a measure of photosynthetic activity/biomass (NDVI). So for example for each sample I have ... Year 2000 2001 2003 ...
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Can two variables be included in same model when if binary B=0, continuous C>0 and when B=1, C=0?

I am interested in looking at the effect of both a binary predictor ("B") and a continuous predictor ("C") on an outcome. However, the value of C is conditional on B in that for B=1, C=0; for B=0, C>0....
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What is the best way to combine “Price” and “Volume” in stock prediction?

I am trying to use LSTM network to predict stock prices. I know in real world there is a relation between the stock price and the trade volume. So I am looking a way to see if is it possible to ...
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1answer
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Scoring procedure for survey responses

I have a project to create a scoring procedure for respondents answering multi choice psychological questions based on their behavioural metrics. So the responses can be treated as categorical ...
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Is it ever okay to ignore a low Cramer's V value?

I conducted a survey on college students to assess what demographic variables affected their views of and knowledge towards climate change. There are 11 variables total: Gender Religion Political ...
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How to use the relaxation algorithm - Time series

Hi I have a linear model where I have to estimate the correlation between the residuals in the calculation of the correlation matrix (as far as i understand). I have the following correlation ...
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1answer
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Can I infer correlation from two time series

Consider the following plot of two variables unemployment and underemployment in different years in the US. Can I infer a positive correlation between unemployment and underemployment? For this ...
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Generating correlated data using numpy while controlling multicollinearity

I am using the following code (adopted from the code in this post). I have no problems with the code. My question is that if with this code I can create or prevent multicollinearity among the ...
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False negative probability of cross-correlation

Suppose $D$ is a string of length $L$ where its values are uniformly distributed in $[-a,a]$. Also, all values of $D$ are independent (i.i.d). $X$ is a noisy version of $D$ in this way: $X=D+N$ where ...
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Correlation between musical knowledge and some measured variables

I have this table: The table shows the occurrences for each feature and separates whether one has or not musical knowledge. I'd like to show in the test column a 'number' that could tell how strong a ...