Describing Statistical Relationships

We've already looked at scatterplots and how to describe relationships between different sets of variables.

Here is a summary of different types of linear relationship:

• Positive relationship: as one variable increases, the other variables also increases.
• Negative relationship: as one variable increases, the other variables decreases.
• No relationship: there is no correlation between the variables.

 

 

Once we can identify the type of relationship between two variables, we can make inferences about these variables and use them in everyday life. For example, say there is a positive relationship between study and results. From this, we can say that the more someone studies, the better they will do in their exams.

Let's look through some more examples now.

 

Examples

Question 1

Identify the type of relationship represented by the following scatter plot.

A) Negative linear     B) No relationship     C) Positive linear

Think: The values on the $x$x axis as representing one variable, and the values on the $y$y axis as representing another variable. How does the $y$y-variable change as the $x$x-variable increases? 

Do: When we look at this graph, we can see that as $x$x-variable increases, the $y$y-variable also increases. So this graph is an example of an A) negative linear relationship.

 

QUESTION 2

 

Question 3