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Understanding Variables and Distributions in Data Analysis

Learn about individuals, variables, categorical and quantitative data. Explore two-way tables, marginal and conditional distribution. Analyze the shape, center, and spread of distributions.

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Understanding Variables and Distributions in Data Analysis

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  1. Adapted from Ms. Namad

  2. Terminology • Individuals- the objects described by a set of data. They may be people, animals, or things. • Variable: any characteristic of an individual. It can take different values for different individuals. • There are two types of variables: categorical and quantitative

  3. Categorical Data • Two-Way Tables: describes two categorical variables • Marginal Distribution: one of the categorical variables in a two-way table of counts is the distribution of values of that variable among all individuals described by the table • Ex: (a+c)/(n)

  4. Categorical Data • Conditional Distribution: variable describes the values of that variable among individuals who have a specific value of another variable • Ex: c/(c+d)

  5. Does the distribution have one or more peaks (modes) or is it unimodal? • Is the distribution approximately symmetric or is it skewed in one direction? Is it skewed to the right (right tail longer) or left?

  6. Shape Left- Skewed Right- Skewed

  7. Example Description • Shape: The distribution is roughly symmetric with a single peak in the center. • Center: You can see from the histogram that the midpoint is not far from 110. The actual data shows that the midpoint is 114. • Spread: The spread is from 80 to about 150. There are no outliers or other strong deviations from the symmetric, unimodal pattern.

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