**364 pearson-r questions.**

Suppose I have the following dataset below:
With my understanding of Pearson's Correlation Coefficient, I could get a coefficient for Percentage Use vs. Average Age between timepoints. However, is ...

I am currently trying to test a model for cross-cultural adaption and need to do a simple correlation analysis between the predictor variables (language ability, adaptive motivation, degree of culture ...

I'm looking to assess whether the difference between a child's response, and their parent's response, to a nearly identical questionnaire is significant or not.
Some papers have used Pearson’s ...

I'm trying to calculate the correlation between the condition number of a finite elements matrix and the coarseness of the mesh that it represents.
However, when trying to calculate the Pearson ...

Get it from someone else but don't quite know how to answer.
If $\rho_{X,Z}=0.4$, $\rho_{Y,Z}=0.3$, what is the range of $\rho_{X,Y}$? Here $\rho$ is the Pearson correlation coefficient.
We run a ...

I am wondering how to derive the formula for the standard error of Pearson's correlation coefficient which is given in Zar for example as
$$
\newcommand{\cov}{{\rm Cov}}
\newcommand{\var}{{\rm Var}}
\...

TL;DR (too long, didn't read):
I'm working on a time-series prediction problem, which I formulate as a Regression problem using Deep Learning (keras). I want to optimize for the Pearson correlation ...

I can understand why it makes sense to maximize $R^2$, but I'm not so convinced that it makes sense to maximize Pearson's $R$. Partially because I don't understand how the "degree of linear ...

I have two time series, spanning about 2.5k observations each. One series is observed values, the other one is predicted values based on a simple linear regression model. Both time series share the ...

I have 2 time-series (both smooth) that I would like to cross-correlate to see how correlated they are.
I intend to use the Pearson correlation coefficient. Is this appropriate?
My second question ...

I am writing a meta-analysis looking at the correlation between different tests for assessing body composition.
The results of the studies that I have included use different ways to calculate the ...

I am a bit confused about how to interpret correlation coefficient results. I am aware that there are numerous questions about the differences between Pearson, Spearman, and Kendall, but I am more ...

Why is it correct not to measure the correlation between two distance matrices by calculating the Pearson's correlation coefficient between all distance pairs but to use the Mantel test instead?
Edit:...

There are very large number of data points ($\sim 10^{100}$), which form a (discrete) joint distribution $(X,Y)$, where $X,Y$ are discrete random variables. Note that we have no knowledge of these ...

When I have two parameters A and B based on 100 values each, I can calculate the pearson correlation coefficient and the confidence interval (95%). If the confidence interval is crossing 0, I can say ...

How do I know when to choose between Spearman's $\rho$ and Pearson's $r$? My variable includes satisfaction and the scores were interpreted using the sum of the scores. However, these scores could ...

I have been reading a paper and I have found a table that felt very strange for me. The researchers have calculated $r$ value and related it to a categorical factor. From my knowledge $r$ is a ...

I am trying to implement k-means clustering on a 6x6 data set that looks like this:2 3 6 0 1 7
4 9 9 6 2 2
0 1 7 9 5 0
2 3 2 7 8 3
8 2 9 2 3 1
8 0 0 1 7 9Using ...

Let say I have this simplified data set which contains four variables (2 categorical, and 2 numerical types):
...

I have the following problem:
I have a dataset of X,Y points and i want to apply a clustering algorithm (in Python) to this dataset. I am trying to find a clever way to avoid applying the clustering ...

I have used a pearson correlation to see if certain variables that other people have found to predict the Dependent variable do occur (so I can use them as covariates later on). I then wanted to do a ...

Suppose I have two sets of Pearson correlation coefficients -- call them set A & set B, and they are of the same size. How do I systematically compare the correlations in A against B? E.g., I want ...

Heres the background, there are a large number of students who enrolled in a very challenging course where it's normal for the drop out rate to be pretty high. Now the school wants to introduce an ...

Almost everywhere I read
If the variables are independent, Pearson's correlation coefficient is 0
I understand that correlation gives information only for linear dependence/independence variables ...

If Spearman correlation is Pearson correlation, but on ranks of the data - does it mean that absolute Spearman will always be lower or equal to absolute Pearson correlation, but never greater? Is it ...

I have two binary variables and want to test their association. From what I've read I need to use the chi-squared ($χ^2$) test. The measure of their association is then described through the Phi ...

Assume there is a population, P, of size N. Each member of the population has three variables associated with it, a nominal variable C (with m unique categories), and two continuous variables X and Y....

I'm a second year psych grad student. From my fascination with formal logic, I wondered (just personal; not homework) about how to statistically establish necessary/sufficient relationships between ...

I've seen some similar articles using R but I'm not sure how to implement this test in python.
Suppose I have two datasets, A and B (both contain 35 datapoints), and they predict some time series of ...

I am giving different doses of a drug to mice and measuring a quantitative response. I want to determine if there is a linear relationship between the dose of the drug and the response. Pearson ...

I understand that r tells us the strength of the linear relationship between two variables, R shows how closely two variables, and β shows which dependent variables would change if we change the ...

The Pearson correlation coefficient of x and y is the same, whether you compute pearson(x, y) or pearson(y, x). This suggests that doing a linear regression of y given x or x given y should be the ...

Say we have a multiple regression model with three predictors and one outcome variable.
Each predictor has it's associated standardized beta, which tells you how many standard deviations the outcome ...

I would like to calculate the correlation between two variables. The first variable is continous and represents a performance measure. The second variable is an integer in the range from one to nine ...

I am trying to draw some statistics out of correlation data and want to better understand two different ways in particular for determining 'significance'... I am not a statistician and have limited ...

I am conducting a meta analysis of Pearson's r , of correlations presented between test scores and job performance ratings. I need to present an uncorrected effect size and an effect size corrected ...

I am conducting a meta analysis of Pearson's r correlations. As there are two correlations , sometimes three , for the same study and dependent variable I have averaged the correlations via fishers z ...

I have calculated two standard errors for two fishers z correlations from the same study , both measuring the same variable. Is it acceptable for me to average the two standard errors into one? If so ,...

I have combined several correlations into fishers z scores for meta analysis. Most of the combined correlations are measuring the same construct within the same study.
I now need to calculate the ...

This is a textbook exercise that might be seen as a generalisation of Pearson's product-moment correlation coefficient between two variables, with multiple groups each having variable sizes:
Let ...

I understand that to calculate the standard error of a pearsons r correlation converted to a z score you follow -
1 / (√N−3)
But how do you calculate the variance from the standard error please? I ...

I am conducting a meta - analysis of pearsons r correlations.I am wondering how I calculate corrected mean population level estimates of the criterion-related validity of each construct domain please?
...

I am conducting a meta analysis of pearsons r correlations and would like to double check my understanding of independent and non- independent effect sizes/correlations.
Am I correct in understanding ...

I have a set of pearsons r effect sizes , converted to fishers z scores for meta analysis. I am wondering what data I need to calculate an inverse variance weight for each effect size and how I ...

I am trying to analyze two variables: Currency exchange rate and Stock price of a company. I am computing the correlation between them to determine whether the currency exchange rate has some effect ...

my meta analysis involves the calculation of overall effect size based on pearsons r correlations within studies. I am already converting the pearsons r to fishers z scores for analysis but I have a ...

There are two interdependent variables - experience and fun. Using a correlation, we can only say how fun and experience are related, and the strength of the relationship. My question is how do I ...

I am interested in whether or not a "correlation" of three variables is something, and if what, what would this be?
Pearson product moment correlation coefficient
$$\frac{\mathrm{E}\{(X-\mu_X)(Y-\...

I'm not entirely sure what I am talking about is Simpson's paradox, because an opposite relationship does not appear when you combine two data sets, but merely a different one. Still, I think it is ...

I apologize if my question is exceedingly simple. Imagine, for example, I am studying a paper which explains that two variables correlate with a certain Pearson's r (no p-value, no confidence interval,...

- correlation
- spearman-rho
- regression
- r
- multiple-regression
- time-series
- p-value
- statistical-significance
- meta-analysis
- spss
- kendall-tau
- hypothesis-testing
- self-study
- confidence-interval
- variance
- python
- chi-squared
- r-squared
- bootstrap
- t-test
- linear
- normal-distribution
- categorical-data
- mean
- sample-size

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