Lecture 17: Correlation Analysis
Æ
Simultaneous analysis of 2 variables
Sources of Information
Motulsky: Chapter 17
Triola et al.:
Chapter 9
Sokal & Rohlf: Chapter 15
Dytham: p. 154-171

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Correlation versus Regression
Correlation
tells us whether there is a relationship between
2 variables and how strong
the relationship is between them.
Î
tells us
how well
the response variable (Y) is predicted
from the predictor variable (X)

Correlation versus Regression
Regression
tells us
how to predict
Y from X
Î
provides the equation to predict Y from X

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Introducing Correlation Analysis
In correlation analysis, we generally want to determine whether two
variables are interdependent, or
covary
– that is, do they vary
together?
Definition
: A
correlation
exists between two variables when one of
them is related to the other in some way.
In common usage, the word ‘correlation’ describes any type of
relationship between objects and events.
In statistical usage, correlation refers to a quantitative relationship
between two variables measured on ordinal or continuous scales.
When we wish to establish the degree of association between pairs of
variables in a sample from a population, correlation analysis is the
proper approach.