Just to refresh your mind Nominal Data (Count Data) is information that you collect about the presence or absence of an attribute (characteristic). Like the number of “naughty” or “nice” kids on Santa’s List. Or, more practical to some, the number of red cars going through an intersection; the number of Order forms with mistakes in them. These counts are all, what we call, nominal scale measurements. This scale of measurement gives us the least amount of information of the four types of measurement scales (Nominal, Ordinal, Interval, Ratio). Scales are ways we collect data. For instance here we are counting the occurrence of something which is what is called a nominal scale.
So once we have done this counting how can we look at the data to see better what we found. Well for this scale there are a few good tools.
Percentage (%) – This gives you a feel for of all the things you saw, how many were what you were looking for. For example lets say you sat at an intersection and counted red cars going through that intersection in one hour. And during that hour you saw 300 cars go through that intersection and 30 were Red. That would mean that for that hour 10% of the cars that went through it were red. (30 red cars/300 cars through the intersection*100=10%).
Proportion (1/10, 1 in 10) – This, like percentage, gives you a feel for of all the things you saw, how many were what you were looking for. This gives you one other piece of information and that is out of how many you looked at. This, if you are doing the study for yourself, may not be important, but if you are convincing others with a percentage they may want to know how many in the total count. A good example where I like this best is on the internet when looking at customer ratings (those stars showing you that customers really liked the product. I always want to know how many customers actually rated the product at all. When you see 1 to 5 I am not impressed. But if there was 100 now I feel better about the rating. Remember that 100% liked something out of 1 (1/1) customer is different that 100 (100/100).
Chi-square Test (X2) – There are many times where we want to compare the percentages of items in several different categories. For instance, instead of just red cars we want to collect the number of all cars by color (not just red). It might be, instead of cars, operators, materials, TV channels, Hospitals or any other grouping we might have in mind. In any of these groups your could collect data and place it into different categories (Colors, Sizes, Ratings). The results can be put into what is called a Chi Square Table to answer the question ”Do the groups differ with regard to the proportion of items in the categories?” An example that one could use Chi-square test would be: (The following example is from Narrella(1963) and the Six Sigma Handbook [Pyzdek, 2003]).
Rejects of metal castings were classified by cause of rejection for three different weeks. The question that the Chi-squared test would help answer is: “Does the distribution of rejects differ from week to week?
Well there you have my thoughts on tools to measure the Nominal Scale. Next time I am going to discuss the different statistical tool used for the ordinal scales of measurement. If, you have questions or comments please feel free to contact me by leaving a comment below, emailing me, calling me, or leaving a comment on my website.
Bersbach Consulting
Peter Bersbach
Six Sigma Master Black Belt
http://sixsigmatrainingconsulting.com
peter@bersbach.com
1.520.829.0090
Tags: Counts, measurement, Method, Nominal data, Six Sigma Process
[...] Contact « Tools to look at Counts (Nominal) Data [...]
[...] this is only non-numeric in the sense that it is data we collect about the presence or absence (nominal data) of some characteristic or attribute of an item. Usually we take this data and transform it into a [...]