What is Pearson Correlation Coefficient?

Pearson-related coefficients (usually short r) are statistical indicators used to measure linear correlations and direction between two continuous variables. Its range of values is strictly limited to [-1, 1]. By calculating the multiplier ratio of the co-variant to the standard difference, r can eliminate the influence of the variable matrix and provide a purely correlation quantification.

How do you interpret the r value scientifically?

r = 1： Perfectly relevant. When X increases, Y always increases precisely in a fixed proportion.
0.8 ≤ |r| < 1： Very relevant. There is a high degree of consistency between variables.
0.5 ≤ |r| < 0.8： Medium intensity is relevant.
0.3 ≤ |r| < 0.5： Weakness.
r = 0： Wireless relationships. Note that this does not mean that there are no other non-linear (e.g., secondary functions) relationships between variables.

Decision factor R2 importance

The determination factor R2 is the square of the relevant coefficient. In regression analysis, it represents the ratio of the total variation due to variable Y, which can be explained by the variable X. For example, if R2 = 0.64, this means that 64 per cent of Y-axis fluctuations can be attributed to changes in the X-axis, which is essential for assessing the reliability of the predictive model.

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