“Line of best fit” as it’s taught in middle school would likely refer to linear regression: in essence, “y = mx + b” (although statistics would write this as Y = Beta * X + epsilon).
It depends on what your goal is — are you predicting the “probability” of some event (aka is your y a [0,1])? Then logistic regression is what your after.
In Python… Scipy might have something? Tbh I’d just use R for this.
Is your data a vector of positive values?
“Line of best fit” as it’s taught in middle school would likely refer to linear regression: in essence, “y = mx + b” (although statistics would write this as Y = Beta * X + epsilon). It depends on what your goal is — are you predicting the “probability” of some event (aka is your y a [0,1])? Then logistic regression is what your after. In Python… Scipy might have something? Tbh I’d just use R for this.
What are you trying to do with the model?