A scatter plot is a data visualization technique to analyze relationships between two variables and find outliers. Understanding **data visualization** graphs is not easy for everyone. So if you want to know how to analyze a scatter plot, this article is for you. In this article, I will take you through a guide on analyzing a scatter plot.

## Structure of a Scatter Plot

A scatter plot visualizes the relationship between two variables where:

- the values of one variable are on the x-axis
- the values of another variable are on the y-axis
- each data point of both variables appears as a point on the graph
- the trend formed by the data points of both variables shows the relationship between both the variables
- any data point that doesn’t follow the pattern is an outlier

I hope you have understood the structure of a scatter plot. The section below will introduce how to analyze a scatter plot.

## Here’s How to Analyze a Scatter Plot

Let’s understand how to analyze a scatter plot by going through some common relationship patterns we see while analyzing scatter plots.

#### When there is a Linear Relationship

The graph below shows a linear relationship between the variable on the x-axis and the y-axis. When the value of one variable increases with an increase in the value of another variable is what a linear relationship means.

In the above scatter plot, we are analyzing relationships between the number of impressions in an Instagram post and the number of followers received from the Instagram post.

When the relationship between the variables shows a straight line starting from 0, it is known as a linear relationship. So, in our example, the linear relationship indicates that the more impressions an Instagram post will have, the more followers you will gain from that post.

There is an outlier in the above graph. It shows an Instagram post resulted in comparatively more followers than other posts with the same number of impressions.

#### When there is an Inverse Linear Relationship

The graph below shows an inverse linear relationship between the variable on the x-axis and the y-axis. When the value of one variable decreases with an increase in the value of another variable is what an inverse linear relationship means.

In the above scatter plot, we are analyzing relationships between the time taken to deliver the food and the overall ratings of the delivery partner based on past deliveries.

When the relationship between the variables shows a straight downward trending line towards 0, it is known as an inverse linear relationship. So, in our example, the inverse linear relationship indicates that the delivery partners with high ratings take less time to deliver the food.

#### When there is No Relationship

The graph below shows no relationship between the variable on the x-axis and the y-axis.

When the relationship between both variables shows a straight horizontal trending line, it indicates no relationship.

### Summary

So below are some takeaways on how to analyze a scatter plot:

- When the relationship between the variables shows a straight line starting from 0, it is known as a linear relationship. When the value of one variable increases with an increase in the value of another variable is what a linear relationship means.
- When the relationship between the variables shows a straight downward trending line towards 0, it is known as an inverse linear relationship. When the value of one variable decreases with an increase in the value of another variable is what an inverse linear relationship means.
- When the relationship between both variables shows a straight horizontal trending line, it indicates no relationship.
- Any data point that doesn’t follow the pattern is an outlier.

I hope you liked this article on how to analyze a scatter plot. Feel free to ask valuable questions in the comments section below.

Awesome!!! Really liked the explanation, just one question, I find hard sometimes what variables to analyze, what variables could be valuable for a scatter plot, could you give me some examples?

Some examples are:

1. Experience vs. Income

2. Price vs. Sales

3. Distance vs. Delivery Time

4. Height vs. Weight

5. Advertising Budget vs. Conversation Rate