pp.12-19 fall 2009

# pp.12-19 fall 2009 - 12 Levels of measurement Data can also...

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Levels of measurement Data can also be classified according to how it is measured, or its level of measurement . The level at which data can be measured is important because it determines what calculations can be performed. The higher the level of measurement, the more informative the analysis that can be performed. Qualitative data use either the nominal or ordinal level of measurement. Nominal level of measurement—used for qualitative variables that can only be categorized and counted. For example, the types of memberships sold at a health club in Columbia (Individual, Family, Trial, or Student) Other examples of nominal level data: Make of car (Ford, Lexus, Toyota, etc.) State of residence (SC, GA, MA, PA, NC, VA, etc) Type of dwelling (house, condo, apartment, etc.) Ordinal level data—qualitative data that can be placed into ordered categories. The orders may be according to which is “best”, or “larger”, or “more preferred”. For example, year in college (freshman, sophomore, junior, senior). 12

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Other examples of ordinal level data include: t-shirt size(S, M, L, XL, XXL) class of air travel (first, business, coach) Award level (gold, silver, bronze) Rankings are also examples of ordinal level data . For example, the top 25 college football teams this year. Quantitative data is measured on either the
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## This note was uploaded on 06/06/2011 for the course MGSC 291 taught by Professor Rollins during the Fall '09 term at South Carolina.

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pp.12-19 fall 2009 - 12 Levels of measurement Data can also...

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