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Lesson 4:
Types of Relationship
Between Variables

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Two truths and one lie

statements in each item are supported with three statements but one of it is a lie. Your task is to choose which among these statements is a lie. ready?

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There are three types of relationship that may exist
between variables. These can be observed by plotting the
gathered data into a graph and can be quantified using
statistical analysis. It is important to understand the
relationship between variables to draw the right
conclusion from this analysis.

Without understanding of this, you can fall into many
pitfalls that accompany statistical analysis and infer
wrong results from your data

Types of Relationship Between Variables

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A relationship between variables that can generally be represented and
explained by a straight line in a scatter plot. Also, it is if you double one
variable, the other will double as well. It is one where increasing variable
(n) times will cause a corresponding increase or decrease of (n) times in
the other variable too.

Linear Relationship

Linear Relationship can be:

●POSITIVE

●NEGATIVE

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A positive linear is a relationship between two variables in which
both variables move in tandem – that is, in the same direction. It
exists when one variable decreases as the other variable
decreases, or one variable increase while the other increases. It
is also called direct relationship.

Positive Linear Relationship

Plot 1: Strong positive linear
relationship. When both variables
increase or decrease concurrently
and at a constant rate, a positive
linear relationship exists.

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A negative linear is a relationship between two variables in which
one variable increases as the other decreases, and vice versa. It
is a relationship between two variables whereby they move in
opposite directions. It is also known as inverse relationship.

Negative Linear Relationship

Plot 2: Strong negative linear
relationship. When one
variable increase while the
other variable decreases, a
negative linear relationship
exists.

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A non-linear relationship is any relationship between variables that does
not fit the definition of a linear relationship. Not linear, which means by
doubling the variable, the other variable will not double. It can be
represented and explained by a line on a scatter plot that is not straight
but curved in some way.

Non-linear relationship

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Indicate that NO relationship is seen between the changes in two
variables. It means that two variables do not follow the same or opposite
trends together. They do not have systematic relationship; changes in one
variable simply are not related to the changes in the other variable.

No Relationship/ Unrelated Relationship