00:01
Once again, welcome to a new problem.
00:05
This time we're dealing with regression analysis.
00:09
We're dealing with regression analysis.
00:13
And under regression, we have the independent x variable, and we also have the dependent y variable.
00:29
The independent is the explanatory variable and the dependent is the response variable.
00:40
So we have both the explanatory variable and we also have the response variable such that the regression equation becomes the same as y hat equals to a plus b.
00:59
If you're using a sample or y hat equals to beta not plus beta 1x remember beta not is the intercept and beta 1 is the slope and also we can always get the regression equation by building a line of best feet this position is the intercept and and of course we have the slope delta y of delta x.
01:34
X is the independent variable.
01:36
Y is the dependent variable.
01:41
We're looking at a new problem.
01:43
And in this particular problem that we're looking at, it deals with wine consumption relative to heart disease.
01:54
So wine consumption becomes your x variable.
01:57
And we also have the heart disease.
02:00
Becomes your y variable.
02:03
These are the two variables that you've given.
02:05
I've also given a regression equation of reflecting the relationship between heart disease and wine consumption.
02:19
So you have those two you have those two relationships and so we can call this the least squares regression equation with a strong moderate relationship.
02:42
We want to predict the heart disease death rate where the adults drink one liter and then also where the adults drink 8 liters.
02:57
So that's what we're going to do using the regression equation.
03:02
So we have y equals to 115 .0 .86 plus 8 .05 times 1.
03:16
And this prediction is going to be the same as, it's going to be the same as 123 .91...