Stats 48 Page 1

# Stats 48 Page 1 - the data exhibit the properties of nominal data and the order or rank of the data is meaningful Interval scale-the data

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Categorical variable - Places an element into one of several groups or categories. Note: arithmetic operations, such as addition and averaging are NOT meaningful for data resulting from a categorical variable. Data are almost always words but could be numbers (ex Gender, Major, zip code) Quantitative variable - Takes numerical values for which arithmetic operations such as adding and averaging make (data are always numbers) ex: gpa, number of classes take/ quarter. Age etc… Scales of Measurement for variables Nominal scale (name) - the data are labels or names used to identify an attribute of an element. (major, gender, brand of fridge etc.) Ordinal scale (order

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Unformatted text preview: )- the data exhibit the properties of nominal data and the order or rank of the data is meaningful. Interval scale-the data demonstrate the properties of ordinal data and the interval between values is expressed in terms of a fixed unit of measure. (Interval data is continuous data where differences are interpretable, but where there is no natural zero. A good example is temperature data. Ratios are meaningless for interval data. You cannot say, for example, that one day is twice as hot as another day. Ratio scale- the data demonstrate all the properties of interval data and the ratio of two values is meaningful....
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## This note was uploaded on 09/13/2011 for the course STATS 10 taught by Professor Christou during the Spring '11 term at UCSD.

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Stats 48 Page 1 - the data exhibit the properties of nominal data and the order or rank of the data is meaningful Interval scale-the data

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