Permutational analysis of variance
Okay, so let's start with a simple game. We have three boxes - Box 1, Box 2, and Box 3. And we have three toys - a basketball, a teddy bear, and a car. We want to see how many different ways we can put the toys in the boxes.
If we just randomly put the toys in the boxes, we will have 3 options for the first toy, 2 options for the second toy (since one box already has a toy), and 1 option for the third toy. So the total number of ways we can put the toys in the boxes is 3x2x1=6.
Now let's imagine that we have a group of kids, and we want to see if there is any difference in the way they put the toys in the boxes. To do this, we can use permutational analysis of variance, or PERMANOVA for short.
PERMANOVA takes the different ways that the toys can be assigned to the boxes and groups them based on similarities. For example, if two kids put the basketball in Box 1 and the teddy bear in Box 2, their toy assignments would be grouped together.
Next, PERMANOVA calculates the differences between the groups to see if there is any significant variation. If the variation is significant, we can say that the way the kids put the toys in the boxes is not random, and there may be something influencing their choices.
So PERMANOVA is like a grown-up version of our toy game. It helps us analyze data to see if there are any patterns or differences that are worth investigating.
If we just randomly put the toys in the boxes, we will have 3 options for the first toy, 2 options for the second toy (since one box already has a toy), and 1 option for the third toy. So the total number of ways we can put the toys in the boxes is 3x2x1=6.
Now let's imagine that we have a group of kids, and we want to see if there is any difference in the way they put the toys in the boxes. To do this, we can use permutational analysis of variance, or PERMANOVA for short.
PERMANOVA takes the different ways that the toys can be assigned to the boxes and groups them based on similarities. For example, if two kids put the basketball in Box 1 and the teddy bear in Box 2, their toy assignments would be grouped together.
Next, PERMANOVA calculates the differences between the groups to see if there is any significant variation. If the variation is significant, we can say that the way the kids put the toys in the boxes is not random, and there may be something influencing their choices.
So PERMANOVA is like a grown-up version of our toy game. It helps us analyze data to see if there are any patterns or differences that are worth investigating.