In the context of linear regression, slopes refer to the coefficients that represent the rate of change between the independent variable and dependent variable. They indicate how much the dependent variable is expected to change for a one-unit increase in the independent variable.
Related terms
Intercept: The intercept represents the predicted value of the dependent variable when all predictor variables are set to zero.
Standard Error of Slope Estimate: The standard error measures how much variability there is in estimating slopes based on random sampling.
Confidence Interval for Slope: A confidence interval provides a range of values within which we can be reasonably confident that the true slope falls.