00:01
Okay, so i see that you need help with this question.
00:02
It says, it says, a psychologist wants to study the effects of the medication drug a and drug b in therapy type group and individual on anxiety levels.
00:12
The anxiety levels for 16 patients are as follows.
00:15
So first thing you have to do is calculate the mean anxiety levels for each group.
00:21
Okay, so for the 20 plus 18, so for the group for drug a, so 20 plus 18 plus, i'm sorry, not 20 plus 18, 20 plus 21 plus 19 plus 20 and divide that by four is 20.
00:49
So that's your mean.
00:51
And then 22 plus 23 plus 24 plus 21.
00:57
Divide that by 4 is 22 .5.
01:01
And then individual 18 plus 17 plus 16 plus 18 divided by 4 is 17 .25.
01:14
And then 19 plus 20 plus plus 21 plus 21, 81 divided by 4 is 20 .25, 20 .25, okay? then you have to set up a hypothesis for anova.
01:35
So you're going to use a two -way anova to test the following hypothesis.
01:42
So the, i'm just going to erase this.
01:44
The null hypothesis is there are no differences in the anxiety levels between the different medications and therapy types.
02:08
The alternative hypothesis is there are differences in anxiety levels between medications and therapy types.
02:22
So when you conduct the two -way anova to perform, you would typically use statistical software like spss or python.
02:33
You need to input the data and specify the model to include both factors, medication and therapy type.
02:42
Type.
02:43
And when you interpret that data after running the anova, you'll get a p -value for the effects of the medication, the effect of the therapy type in their interaction.
02:57
If the p -value is less than 0 .05, you reject the null hypothesis, okay, for that effect...