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Unformatted text preview: Looking at data: distributions Displaying distributions with graphs IPS chapter 1.1 Objectives (IPS chapter 1.1) Displaying distributions with graphs Variables Two types of variables Ways to chart categorical data Bar graphs Pie charts Ways to chart quantitative data Stemplots Histograms Time Plots Interpreting histograms Variables In a study, we collect informationdatafrom individuals . Individuals can be people, animals, plants, or any object of interest. A variable is a characteristic that varies among individuals in a population. Example: age, height, blood pressure, ethnicity, leaf length, first language The distribution of a variable tells us what values the variable takes and how often it takes these values. Two types of variables Variables can be either quantitative Something that can be counted or measured for each individual and then added, subtracted, averaged, etc. across individuals in the population. Example: How tall you are, your age, your blood cholesterol level, the number of credit cards you own or categorical. Something that falls into one of several categories. What can be counted is the count or proportion of individuals in each category. Example: Your blood type (A, B, AB, O), your hair color, your ethnicity, whether you paid income tax last tax year or not How do you know if a variable is categorical or quantitative? Ask: What is being recorded about the individuals/units? Is that a number ( quantitative) or a statement ( categorical)?...
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This note was uploaded on 05/09/2009 for the course PAM 2100 taught by Professor Abdus,s. during the Spring '08 term at Cornell University (Engineering School).
 Spring '08
 ABDUS,S.

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