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Univariate Data: Definition, Analysis & Examples

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  • 0:01 Definition of Univariate Data
  • 0:54 Reasons to Use Univariate Data
  • 2:17 A Univariate Research Analysis
  • 4:31 Lesson Summary
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Lesson Transcript
Instructor: Tracy Payne, Ph.D.

Tracy earned her doctorate from Vanderbilt University and has taught mathematics from preschool through graduate level statistics.

How does the variable vary? This calls for a univariate analysis. There is a lot of information that can be garnered using univariate data. This lesson describes this type of data and the analyses conducted with it.

Definition of Univariate Data

How many months does it take for avocado plants to produce their fruit? Which illnesses cause the greatest number of deaths? What is the maximum number of children who can ride safely on a schoolbus? What is the typical net worth of an American family? Each of these questions can be answered using univariate data. Univariate data is a collection of information characterized by or depending on only one random variable.

Take for example the last question: what is the typical net worth of an American family? We are interested in how responses vary from person to person when asked about their family's net worth. Only, no one would answer this question by providing every response received to the question. Instead, we would want to summarize the data using statistics that represent the majority of people in the population for whom the question is being asked.

Reasons to Use Univariate Data

Data is gathered for the purpose of answering a question, or more specifically, a research question. Univariate data does not answer research questions about relationships between variables, but rather it is used to describe one characteristic or attribute that varies from observation to observation. To describe how net worth varies, we would use univariate data to find the statistics that represent the center value for all American households along with how the other values spread from that center value.

A researcher would want to conduct a univariate analysis for two purposes. The first purpose would be to answer a research question that calls for a descriptive study on how one characteristic or attribute varies, such as describing how net worth varies from American family to American family.

A second purpose would be to examine how each characteristic or attribute varies before including two variables in a study using bivariate data or more than two variables in a study using multivariate data (bivariate data being for a 2-variable relationship and multivariate data being for a more than 2-variable relationship). For example, it would be beneficial to examine how net worth per family varies before including it in an analysis that correlates it with a second variable, say, educational attainment.

A Univariate Research Analysis

The statistics used to summarize univariate data describe the data's center and spread. There are many options for displaying such summaries. The most frequently used illustrations of univariate data are:

  • Frequency distributions
  • Histograms
  • Stem and leaf plots
  • Box and whisker plots
  • Pie charts

The measures of central tendencies each tell us something different about the data, and each measure has advantages and disadvantages to its use.

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