![]() Temperature scales like Celsius (C) and Fahrenheit (F) are measured by using the interval scale. ![]() The differences between interval scale data can be measured though the data does not have a starting point. But the differences between two pieces of data cannot be measured.ĭata that is measured using the interval scale is similar to ordinal level data because it has a definite ordering but there is a difference between data. A cruise survey where the responses to questions about the cruise are “excellent,” “good,” “satisfactory,” and “unsatisfactory.” These responses are ordered from the most desired response to the least desired.The top five national parks in the United States can be ranked from one to five but we cannot measure differences between the data. A list of the top five national parks in the United States.Like the nominal scale data, ordinal scale data cannot be used in calculations. Some people may favor Apple but that is a matter of opinion.ĭata that is measured using an ordinal scale is similar to nominal scale data but there is a big difference. This is just a list and there is no agreed upon order. Some examples are Sony, Motorola, Nokia, Samsung and Apple. ![]() Smartphone companies are another example of nominal scale data.Putting pizza first and sushi second is not meaningful. To classify people according to their favorite food, like pizza, spaghetti, and sushi.Nominal scale data cannot be used in calculations. Categories, colors, names, labels and favorite foods along with yes or no responses are examples of nominal level data. They are (from lowest to highest level):ĭata that is measured using a nominal scale is qualitative. Data can be classified into four levels of measurement. Not every statistical operation can be used with every set of data. Correct statistical procedures depend on a researcher being familiar with levels of measurement. The way a set of data is measured is called its level of measurement.
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