The correlation coefficient, r, measures the extent of the correlation between two variables.
A correlation between two variables (ice-cream consumption and shark attacks) may well be due to a third variable (summer weather).
An observational study, however, shows only a correlation between two variables (e.g., level of HDL and number of heart attacks).
Pearson's correlation coefficient (R) calculates the correlation between two variables.
A correlation of + 1 indicates a perfect positive correlation between two variables.
The correlation between two variables reflects the degree to which the variables are related.
The larger the absolute value of r is, the stronger correlation between two variables is.
However, positive correlation between two variables indicate that one variable will increase or decrease with respect to other changes and negative correlation between two variables indicate one variable will increase when other will decrease and vice versa.
Value of Karl pearson's correlation coefficient was 0.95311, indicating a high degree of correlation between two variables.
Pearson-correlation coefficient provides a value between +1 and -1 by measuring the linear correlation between two variables.
Pearson Correlation is one of the most widely-used functions to measure the linear correlation between two variables.
