Chapter 2 notes - Statistics Variables and Data...

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Statistics Variables and Data Variable—characteristic that varies from one person or thing to another Height Weight Number of siblings Sex Marital status Eye color
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Statistics Variables and Data 2 types of variables Quantitative variables Height Weight Number of siblings Qualitative variables Sex Marital status Eye color
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Statistics Variables and Data 2 types of quantitative variables Discrete—variable whose possible values can be listed, even though the list may continue indefinitely Number of siblings Number of watches Continuous—variable whose possible values form some interval of numbers Height Weight
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Statistics Variables and Data Data—information collected, organized, and analyzed Qualitative data—data obtained by observing values of a qualitative variable Quantitative data—data obtained by observing values of a quantitative variable Discrete data—data obtained by observing values of a discrete variable Continuous data—data obtained by observing values of a continuous variable Observation—each individual piece of data Data set—collection of all observations for a particular variable
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Statistics Grouping Data Grouping—putting data into groups rather than treating each observation individually Frequency—the number of observations that fall in a class Frequency distribution—a listing of all classes and their frequencies Relative frequency—the ratio of the frequency of a class to the total number of observations
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Statistics Grouping Data Lower cutpoint—the smallest value that could go in a class Upper cutpoint—the smallest value that could go in the next higher class—also the same as the lower cutpoint of the next higher class Midpoint—the middle of a class, obtained by taking the average of its lower and upper cutpoints Width—the difference between the upper and lower cutpoints of a class
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Grouping Data The following guidelines should be used when constructing a Frequency Distribution from a Data Set. Decide on the number of classes to include in the frequency distribution. Usually between 5 and 20 classes are considered appropriate. Find the class width. Use the formula: Class width = difference in maximum data entry and minimum data entry divided by the number of classes. Find the class limits.
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This note was uploaded on 09/12/2008 for the course MATH 1431 taught by Professor Unkown during the Spring '08 term at Georgia Perimeter.

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Chapter 2 notes - Statistics Variables and Data...

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