Thank you for making this video. In short, a 95% confidence interval catches the true mean for 95 times out of 100. 95% prediction interval catches the individual y generated by the true mean 95 times out of 100. Visual explanation around 14:40 is very helpful. Thank you again!
Yes for some reason i did not understand confidence vs prediction interval when it is shockingly simple. The visual is helpful but i think the explanation could be much improved starting from previous videos.
Hi, Brandon. Thank you so much for making these videos as they are a big help (reference source) in helping in the learning process of my University students. Keep up the good work!
Those videos have helped me a lot.!!!! I can't wait to watch more and more videos~~~ (( I have a Statistic midterm exam in the next week.......TAT 感恩版主，等不及看更多影片了(下禮拜是統計學期中考，這些影片拯救了我!!!
I think what doesn’t make it clear in many videos and lecture notes is that the prediction interval is the interval of the population regression line in which an observed y value is in , is this correct ?
@14:46 If we are combining two variances of the star marks and the dots together to get the prediction interval, then won't the star variances and dot variances overlap each other causing double addition?
Thanks Brandon. How is the prediction interval different from just using the regression equation to predict a value of y (at a given level of confidence?). Which approach would you use if you were trying to do predictive analysis?
In population, the Y distribution is an actual value, not estimated. So if we use a population data, does PI band equal CI band? Thank you so much for the VDO.
At 9:29 , how does the software predict a negative value for the lower bound of the tip if the bill is 34$ or 51$? That doesn't seem feasible in reality.
Nice video's! If there would be for example 2 restaurants at which the tips were analysed, how could we then calculate the 95% CI of the difference in tip amount at $64? Or with other words, how can we calculate at a certain point in two regression lines if the difference between them is significant? Should I use the 95% prediction interval or the 95% CI?
Great video, Thanks a lot! But wait, isn't Sy*-squre for the mean of E(y*) from your last video (Statistics 101: Linear Regression, Confidence Bands - Part 2 of 2,) in which you used Sy* square to calculate confidence interval, would you please give deep explain?
The mean value of the actual population of tips on a $64 bill is the average of a lot of possible tips given, whenever the bill happens to be $64. The individual value is an attempt to estimate what the tip will be one particular time that the bill is $64. We can calculate averages a lot more confidently than we can one particular outcome. One particular outcome is more affected by random chance. That is why the '1' is added in, under the radical sign, to enlarge the whole 'give or take' quantity after the plus-or-minus sign.
Hi Brandon, At 19:06, shouldn't the (64-74)^2 values be values of the IDV instead of the dependent variable? or am I misunderstanding something? thank you always!
