Bivariate Statistics and Linear Models

Shravan Vasishth () and Michael Broe ()
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Shravan Vasishth: University of Potsdam, Department of Linguistics
Michael Broe: Ohio State University, 1304 Museum of Biological Diversity, Department of Evolution, Ecology & Organismal Biology

Chapter Chapter 6 in The Foundations of Statistics: A Simulation-based Approach, 2011, pp 127-143 from Springer

Abstract: Abstract So far we’ve been studying univariate statistics; for example, for each individual in a population, we take a single measurement, height, age, etc. We combine these into a sample and compute a statistic: mean, variance, or some function of the variance. Now we consider the scenario where, for each individual in a population, we have two values: age and height, midterm and final exam result, etc. In such a situation we can, of course, treat each dimension independently, and compute the same univariate statistics as before. But the reason we measure two values is to assess the correlation between them, and for this, we require ‘two-dimensional’ or bivariate statistics.

Date: 2011
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DOI: 10.1007/978-3-642-16313-5_6

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