00:01
For this problem, in part a, we have that the null hypothesis for the relevant test here is going to be that all mean weights are equal.
00:17
The alternative hypothesis would be that at least one mean differs significantly.
00:37
For part b, we'll have to go into r.
00:40
So the first thing that we need to do is make sure that we have our chick weights data set loaded into our local environment.
00:47
So i do data, check wts.
00:49
So we can see that that has been loaded in.
00:51
We have 71 observations of two variables.
00:55
Now for part b, we're asked to calculate the mean final weight for each diet group using r.
01:01
So we can say mean weight.
01:06
Now we have six different groups here.
01:09
So the most efficient way to do this is going to be to use the aggregate function in r.
01:15
So we can say we want to to aggregate our data, we specifically are interested in the chick weights, and we are interested in the weight, then we specify what we are aggregating by.
01:33
In this case, we're aggregating by the diets.
01:37
So chick weights, dollar side, feed...