Comparison of unranked categorical data

Which line of code will compare the observed values to the values that are expected according to Mendelian inheritance?

If you have 2 groups with 2 unranked categories each, which test do you need to compare them?

I want to compare males’ and females’preferences for cats and dogs using a Fisher test. What data type do I need to store the data in?

I create the matrix as follows:

Pets <- cbind(“F”=c(78,30),”M”=c(40,31))

Such a matrix with counts (how many persons fall in each category) is called a contingency table.

The only thing that is missing are row names. Which line of code will add the names of the categories as row names to the matrix?

I created the contingency matrix as follows:

Pets <- cbind(“F”=c(78,30),”M”=c(40,31))
rownames(Pets) <- c(“Cat”,”Dog”)
Pets
        F   M
Cat 78 40
Dog 30 31

I asked girls and boys if they prefer cats or dogs so there are two groups: males and females and two categories: cats and dogs. 

Now perform the Fisher test on the contingency matrix. Is there a difference between males and females?

This time I want to compare two groups with each three categories. Which test do I need?

This time I ask boys and girls if they prefer cats, dogs or llamas. I create the contingency table as follows:

Pets <- cbind(“F”=c(78,30,46),”M”=c(40,31,47))
rownames(Pets) <- c(“Cat”,”Dog”,”Llama”)
Pets
        F   M
Cat 78 40
Dog 30 31
Llama 46 47

I still have 2 groups: males and females but now I have 3 categories: cats, dogs, llamas. Because there are > 2 categories I have to do a chi square test. 

Do the test and check if there’s a difference between girls and boys?