Add a variable to indicate the total. In this case, 6 months is half a year, so we will call this variable "half". Sample data below for columns A,B,C
![enter image description here](https://i.stack.imgur.com/J2VAw.png)
Now set up a pivot table with both half and month as rows and sales as the value, as shown below.
![enter image description here](https://i.stack.imgur.com/TwdwG.png)
It sounds like you are asking a lot of different questions here.
My question is: how should I interpret the p value? I don't understand what is that referred to.
The null hypothesis for Fisher's Exact test is that the groups do not affect the outcome, i.e. that they are independent. Rejection of the null hypothesis indicates the outcome (a, b, or c) is dependent on group.
fisher.test(matrix(c(2, 12, 1, 5, 3, 1),
nrow=2, ncol=3, byrow=TRUE))
Fisher's Exact Test for Count Data
data: dta
p-value = 0.05082
alternative hypothesis: two.sided
In this case your $p$ value is approximately 0.05082. I will let you decide whether to reject the null.
Having the p value, how can I say that one of the three forms is statistically significant more represented than the others (if true)?
This is a separate question and I'm not sure what you are trying to ask.
Best Answer
You may create a contingency table using a software tool called pivot table :)
A contingency table is a crosstable with rows, columns and data related to each of the row/column combination. You may draw such a table on a piece of paper, you may use an OLAP cube as the source of data etc. As this site says, a contingency table is essentially a display format used to analyse and record the relationship between two or more categorical variables.
A pivot table is one of the possible ways of creating a contingency table. A typical pivot table has the visual form of the contingency table, although a pivot table might have only one column or even zero etc. The pivot operation in spreadsheet software can be used to generate a contingency table from sampling data. However you may use the pivot table as a tool to play with the data in other ways, too.