00:01
All right, so we're giving some data on the age of cars and the minimum stopping distance at 40 kilometers an hour.
00:06
And we're looking at how the age of a car affects their braking capability.
00:14
So a lot of this work is meant to be done in a spreadsheet or it's more easily done in a spreadsheet and just knowing how to manipulate it.
00:23
And that's a lot of what we do with statistics.
00:26
So here we want to identify the dependent and independent variable.
00:30
So the independent variable is going to be our age.
00:52
And then the stopping distance is going to be the dependent.
01:01
And the reason for that is because the stopping distance wouldn't determine the age.
01:06
It's the age would determine the stopping distance.
01:08
That's the most reasonable conclusion to make here.
01:13
And so this is our x.
01:16
The age and month is our x.
01:19
And the stopping distance is our y.
01:23
And we are told to find the regression equation, y equals a plus bx, given the formula for b and for a, where b is like the slope of that regression line is the y intercept.
01:42
And then we're going to use that line to make a prediction.
01:48
So a lot of this work is, like i said, it's in the spreadsheet.
01:52
So i took the data, put into a spreadsheet, the age, stopping distance here.
01:57
You need the sum.
02:01
We need to take the sum of the product of x and y.
02:05
So i have a column for each x times its corresponding y.
02:08
That's what this colon is.
02:10
It's little those values.
02:11
And then down here, this is the sum.
02:13
So i have this sum row here.
02:15
This is the sum of the x's, some of the y's, some of the x, y's...