I am novice when it comes to data analysis, though I find myself doing it a lot. I apologize if this question has a simple answer that I am not seeing.
I have a frequency table of medical interventions done during an emergency that are graded as "not done", "poorly done", and "well done". The data includes out of the total number of groups, how many were graded as "not done", "poorly done", and "well done" for each medical intervention. The goal is to see how the teams performed during the emergencies and identify areas for improvement. See example table.
Is there any way I can analyze this in a way where we can generate p-values for each intervention? If not p-values, what is the best statistical method by which to analyze it? I am not looking for mean, median, mode but something more statistical. I am open to combining "not done" and "poorly done" if that would be better for analysis.
I looked into chi-squared analysis but I cannot seem to find appropriate values for the "expected". I looked into analysis for ordinal data but I am not sure if this is really even considered ordinal, or what exactly my independent and dependent variables would be. I tried the method of ="((total1 * total2) / total sample size" to get expected values but the p-values I received did not make much sense. I have used both Excel and R to do the analysis for this. I would like something more than just descriptive statistics to solidify and make statements about the problem.
UPDATE: I tried doing the analysis with a one-sample Z-test with the accepted value for the interventions being 100% well done (since I assume that is what we expect in healthcare). However, p-values are all very small since 100% is not really a feasible expectation. I can use this but I am not sure if it is statistically sound.