00:01
So they took some random data on the costs of some meals, and we'll be assuming that the mean cost for an italian meal is equal to that of a seafood is equal to that of a steakhouse restaurant.
00:14
And alternately, that not all the means are equal or the same.
00:23
Now we're going to use an alpha level of 0 .05, which seems to be consistent.
00:27
Now, i have entered all of my data into list one, list two, and list three, and i'm going to perform an anova with my software.
00:37
And we'll fill in the table.
00:40
So we have the treatment.
00:41
We have the air.
00:44
And they also call the treatment the factor and the total.
00:47
And we'll have the sum of squared.
00:50
We'll have the degrees of freedom, the mean square, the f statistic, and the p value.
00:56
And so when we get that, we find that the sum of squared is 208, and the degrees of freedom is 2, which leaves us a the quotient gives us a 104 for the mean square for the treatment.
01:11
And for the air, we have that value as 298, with degrees of freedom being 21, which is the total number of pieces of data, 24, less 3 because of the three categories or three treatments.
01:27
And then dividing these two gives us our mean square, which is 14 .190.
01:33
And then you can total these up.
01:35
This is going to be 16 carry the one.
01:38
That's going to be 506.
01:40
If you want that total, and this is going to end up being 23.
01:43
And then our f statistic is to take the quotient of these two...