# Correlation Coefficient
measures the strength of relationship between variables.
# Linear Regression
see connection between 2 variables - where one variable is dependand & the other one is independant. a regression-line gets customized, that it can deliver the best predictions for the dependant variable based on the independant variable.
Example: weight depends on height
- height = d + k * x
# P-Value (%)
is a statistical number, that represents the propability, that something happens naturally or if it is random. If it is “fair” or “not fair”.
Example with a coin:
- when you throw a coin & you flip it there is the same propability for head or number.