2.10:

2.10: Scatter Plot

JoVE Core
Statistics

A subscription to JoVE is required to view this content. Sign in or start your free trial.

JoVE Core Statistics

Scatter Plot

2.11: Time-Series Graph

6,914 Views

•

01:15 min

•

April 30, 2023

Overview

The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:

High values of one variable occurring with high values of the other variable or low values of one variable occurring with low values of the other variable.
High values of one variable occurring with low values of the other variable.

One can determine the strength of the relationship by looking at the scatter plot and seeing how close the points are to a line, a power function, an exponential function, or to some other type of function. For a linear relationship, there is an exception. Consider a scatter plot where all the points fall on a horizontal line providing a "perfect fit." The horizontal line would, in fact, show no relationship.

When looking at a scatterplot, one must notice the overall pattern and any deviations, if any.

Transcript

Consider quantitative data on the price of houses and their corresponding ground area. Such quantitative data with two variables are called bivariate data.

The variable that acts as the cause is called the independent variable, while another variable that shows the response is called the dependent variable.

This dependence of one variable over the other can be visualized using the scatter plot. Here, the independent variable—the ground area—is represented along the X-axis, and the dependent variable—the price of houses—is represented along the Y-axis.

Mark the prices corresponding to the ground area. Then, draw the best fit line such that an almost equal number of points are present above and below this line. These points together form the pattern to identify the correlation between the two variables.

Notice that the increase in the ground area leads to a rise in the price of houses. Such an increasing trend denotes a positive correlation.

Conversely, if one observes a decreasing trend, it indicates a negative correlation. No trend means no correlation.

Key Terms and definitions

Scatter Plot - A graph showing the relationship between two variables, x and y.
Direction - Highs and lows of variables in a scatter plot.
Perfect Correlation - All points in a scatter plot fall on a single line.
No Trend - Scatter plot showing no clear relationship between variables.
Linear Relationship - Scatter plot where data points fall along a line, but not horizontally.

Learning Objectives

Define Scatter Plot - Visual representation of the relationship between two variables (e.g., scatter plot).
Contrast Perfect Correlation vs No Trend - Distinguish between clear and unclear relationships (e.g., perfect correlation scatter plot vs no trend scatter plot).
Explore Examples - Look at variations of scatter plots (e.g., linear relationship scatter plot).
Explain Scatter Plot Direction - Describe how the direction of a scatter plot is determined.
Apply in Context - Understand how scatter plots are used in psychology.

Questions that this video will help you answer

What is a scatter plot and how to read one?
What distinguishes perfect correlation from no trend in scatter plots?
How to determine the direction of a scatter plot?

This video is also useful for

Students - Understanding of scatter plots aids in comprehending variable relationships.
Educators - Scatter plots provide a visual tool for teaching relationship between variables.
Researchers - Scatter plots can serve as a fundamental tool in data analysis.
Science Enthusiasts - Scatter plots offer a simple way to see relationships between variables.

Tags

Grafico a dispersione Relazione Variabili X e Y Valori alti Valori bassi Forza della relazione Relazione lineare Prossimità dei punti Adattamento perfetto Modello generale Deviazioni