Karl Pearson Correlation and Regression

 Karl Pearson Correlation Coefficient

 Simply known as Pearson's r, it is a statistical measure used to calculate the strength and direction of the linear relationship between two variables, usually denoted as x and y.

WEATHER CONDITIONS DATA

The correlation is very weak (close to 0). 

The negative sign means that as x increases, $y$ tends to decrease slightly, but the relationship is extremely weak.

REGRESSION

Regression is a statistical method that models and analyzes the relationship between a dependent variable and one or more independent variables .

 Linear regression is the relationship between one independent variable  x and one dependent variable y.

Conclusion 

In this data, there is a very weak, negative relationship between $x$ and y. As $\mathrm{x }$increases, $\mathrm{y }$decreases slightly, but the relationship is not strong enough to make confident predictions.