# Fisher test of a Likert survey

For my thesis i have to find out if there is any statistical correlation between a Traditional+Experimental teaching method (compared to a merely traditional one) and a highier level of understanding of certain subjects.

I used a survey structured on a likert scale of 4 (Strongly agree/disagree), with two sets of questions for each subject.

• First survey: "TRADITIONAL teaching method has helped in the
understanding of x" "i strongly agree/disagree"
• EXP. lessons completed
• Second survey: "EXPERIMENTAL teaching method (on top of a traditional one) has helped in the understanding of x"

Where x are 4 different kinds of specific notion/subject.

I used fisher test because i have a low total count(8 people). Code in R, with the first set of data for x1, looked something like this

input_mxn_table = structure(list(Standard = c(0L, 5L, 2L, 1L), Tread = c(1L, 5L, 1L, 1L)), .Names = c("Standard", "St+Experimental"), row.names = c(NA, -4L), class = "data.frame")

fisher.test(input_mxn_table)


The results look realistic as in 3 out of 4 subjects there is no improvement that is statistically relevant. But does this make sense? Did i make any mistake (logic or code)?

• And what are the rows (1, 2, 3, 4)? Are those the four subjects? Or are those the four Likert response categories? Commented Jul 25, 2018 at 17:39
• The same eight people took both surveys? Commented Jul 25, 2018 at 17:40
• The table is a table of counts, not Likert scores? Commented Jul 25, 2018 at 17:46
• 1) the four response categories (strongly agree/disagree) 2)yes 3)Counts, how many people answered with one of each of the four responses(for each of the total subjects) Sorry if i wasn't clear enough
– Bos
Commented Jul 25, 2018 at 21:06