@@briangreco2718 But the regression here is drawn with origin as 0. also the regression line is cutting the Y axis somewhere between 50-100, lets assume 75. so it shows when x=0, y=75, which basically is the intercept. I am a bit confused on this. how is the intercept -500 and the graph shows something else
The graph doesn’t show the x=0, so you are reading the graph incorrectly. The equation is correct and you understand the equation correctly, but you are reading the graph incorrectly. There is no y axis.
this is crystal clear explaination
wow Thankyou Brian, very clear explaination
crystal clear, well done!
This is the most amazing and simple explanation I've seen so far, good job mate.
Thank you, I appreciate it!
Fantastic sir. ❤ Thanks a lot 🙏🙏🙏
You should explain why the differences are Squared.
Great idea, Jim. That gives me an idea for a future video, talking about absolute versus squared differences and why we use squared errors. Thanks!
good explanation
Thankyou very much......
At first I thought this was about R^2 like just the variable squared and not the regression coefficient. :-O
cheers
can you explain why is your intercept -500? the diagram shows that the intercept of the line should be positive. so why is it negative?
The y-intercept is not shown on the graph at all, because the x axis only goes from 60 to 70. X = 0 is way to the left.
@@briangreco2718 But the regression here is drawn with origin as 0. also the regression line is cutting the Y axis somewhere between 50-100, lets assume 75. so it shows when x=0, y=75, which basically is the intercept. I am a bit confused on this. how is the intercept -500 and the graph shows something else
The graph doesn’t show the x=0, so you are reading the graph incorrectly. The equation is correct and you understand the equation correctly, but you are reading the graph incorrectly. There is no y axis.
a.k.a brier score
Brier score is more specifically for predictions of binary events, but yes they are very similar!