| pearson {math} | R Documentation |
Correlation is a statistical measure that indicates
how strongly two variables are related. It involves
the relationship between multiple variables as well.
For instance, if one is interested to know whether
there is a relationship between the heights of fathers
and sons, a correlation coefficient can be calculated
to answer this question. Generally, it lies between
-1 and +1. It is a scaled version of covariance and
provides the direction and strength of a relationship.
this function measure a Parametric Correlation – Pearson correlation(r):
It measures a linear dependence between two variables (x and y)
is known as a parametric correlation test because it depends on
the distribution of the data.
Pearson Rank Correlation is a parametric correlation.
The Pearson correlation coefficient is probably the most
widely used measure for linear relationships between two
normal distributed variables and thus often just called
"correlation coefficient".
pearson(x, y,
MAXIT = 5000);1. r takes a value between -1 (negative correlation) and 1 (positive correlation). 2. r = 0 means no correlation. 3. Can Not be applied to ordinal variables. 4. The sample size should be moderate (20-30) For good estimation. 5. Outliers can lead To misleading values means Not robust With outliers.