如何理解皮尔逊相关系数（Pearson Correlation Coefficient）？
Pearson相关性系数（Pearson Correlation） 是衡量向量相似度的一种方法。 输出范围为-1到+1, 0代表无相关性，负值为负相关，正值为正相关。
How to choose between Pearson and Spearman correlation?
Mar 2, 2017 · The difference between the Pearson correlation and the Spearman correlation is that the Pearson is most appropriate for measurements taken from an interval scale, while the …
如何理解皮尔逊相关系数（Pearson Correlation Coefficient）？
Pearson 相关系数 （Pearson Correlation Coefficient，常简称 PCC，非 “Person 相关系数”），它是统计学中衡量 两个连续变量之间线性相关强度与方向 的经典指标，由英国统计学家卡尔・ …
machine learning - What's the correct approach to measure …
Dec 22, 2021 · Binary & Continuous: Point-biserial correlation coefficient -- a special case of Pearson's correlation coefficient, which measures the linear relationship's strength and direction.
Methods For Measuring Non-Linear Correlation? - Cross Validated
Nov 9, 2022 · Pearson Correlation Coefficient measures the linear correlation between two sets of data Spearman's Correlation measures the "monocity" between two sets of data (e.g. do they …
How to use Pearson correlation correctly with time series
Jan 13, 2015 · 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 …
do logs modify the correlation between two variables?
Dec 8, 2014 · The most common one is Pearson's correlation coefficient, which measures the amount of linear dependence between two vectors. That is, it essentially lays a straight line …
Why is Pearson parametric and Spearman non-parametric
Mar 17, 2015 · 3 I think the only reason why Pearson's correlation coefficient would be called parametric is because you can use it to estimate the parameters of the multivariate normal …
Pearson's or Spearman's correlation with non-normal data
When the variables are bivariate normal, Pearson's correlation provides a complete description of the association. Spearman's correlation applies to ranks and so provides a measure of a …
When is $R^2$ the same as Pearson's $r$ squared?
Most explanations I have read says that $R^2$ can be derived by squaring the Pearson's $r$, and hence the name. However, using the formulas given above, then a squaring of $r$ does not …