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Levels of Measurement

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+ The levels of measurement are a way of categorizing a data as one of four different categories: +

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Ratio Data

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Interval Data

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Ordinal Data

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Nominal Data

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+ An example of nominal data is blood types: +

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  • type A+
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  • type A-
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  • type B+
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  • type B-
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  • type AB+
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  • type AB-
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  • type O+
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  • type O-
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+ Another example of nominal data is sex: +

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  • female
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  • male
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+ Another example of nominal data is family names: +

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  • Alves
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  • Beg
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  • Chen
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  • Cho
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  • Choi
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  • da Silva
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  • Dickson
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  • dos Santos
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  • Esfahani
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  • Fernández
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  • Ferreira
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  • García
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  • Jung
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  • Kang
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  • Kerr
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  • Kim
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  • Krempeaux
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  • Li
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  • Liu
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  • Martin
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  • Müller
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  • Pahlavi
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  • Park
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  • Parsi
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  • Pereira
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  • Rodríguez
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  • Safavi
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  • Sasani
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  • Wang
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  • Yun
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  • Zhang
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  • etc
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+ Another example of nominal data is hair color: +

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  • brown
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  • black
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  • blond
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  • gray
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  • red
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  • etc
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+ Another example of nominal data is cities: +

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  • Beijing
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  • Bangalore
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  • Bangkok
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  • Bogotá
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  • Buenos Aires
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  • Cairo
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  • Chennai
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  • Chicago
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  • Chongqing
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  • Dallas
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  • Delhi
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  • Dhaka
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  • Guangzhou
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  • Hyderabad
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  • Kinshasa
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  • Kolkata
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  • Isfahan
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  • Istanbul
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  • Jakarta
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  • Karachi
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  • Lagos
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  • Lahore
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  • Lima
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  • London
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  • Los Angeles
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  • Moscow
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  • Nagoya
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  • New York City
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  • Osaka
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  • Manila
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  • Mexico City
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  • Mumbai
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  • Paris
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  • Rio de Janeiro
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  • São Paulo
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  • Seoul
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  • Shanghai
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  • Shenzhen
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  • Tehran
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  • Tianjin
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  • Tokyo
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  • Toronto
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  • Vancouver
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  • etc
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Operations

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+ One way of understanding the levels of measurement is — what type of operations are meaningful and valid for that type of data‽ +

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+ Here is a table that summarizes what operations are and are notmeaningful and valid for each levels of measurement category: +

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nominalordinalintervalratio
can × and ÷ ?nononoYES
can + and - ?nonoYESYES
can < and > ?noYESYESYES
can = and ≠ ?YESYESYESYES
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