A scatter diagram , also known as a scatter graph or scatter plot in English, is a graphical tool used to observe and analyze the relationship between two variables. This type of graph represents data as a set of points on a Cartesian plane, where each point corresponds to the values of two variables.
It is especially useful in statistical studies and correlation analysis, Czechia Email List allowing the identification of patterns, trends and possible anomalies in the information. Furthermore, its simplicity and clarity make it an accessible option even for those without a technical background in statistics.
Scatter plot template illustrating sea level and temperature in different years.
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Understanding the scatter plot
A scatter plot is a graph that shows the relationship between two continuous variables. In this graph, each point on the Cartesian plane represents a pair of values corresponding to a single observation of the two variables in question.
For example, if we are analyzing the relationship between height and weight of a group of people, each point in the diagram would represent the height and weight of each individual. By looking at how the points are distributed, we can identify whether there is a positive, negative, or no relationship between the variables. This visualization makes it easier to spot patterns and trends, as well as identify potential outliers.
Example of a Cartesian plane showing how a point is located between the X and Y axes
Example of Cartesian plane via: UNAM
Objectives of scatterplot
These scatter plots have several key objectives in data analysis that can help you gain insight. Some of these objectives include:
One of the main goals is to identify relationships between two specific variables. Another goal is to identify and analyze general patterns in large sets of f. This includes identifying linear trends, such as a steady increase in the value of a variable over time, as well as non-linear trends, where changes may follow a curve rather than a straight line.
Another objective of this type of graph is that it helps to observe how the data is distributed around a trend line, providing information about its variability. Finally, it can be mentioned that they provide a clear and accessible visual representation of the information, allowing easy interpretation even for people without technical training in statistics.
These objectives make the scatter diagram an essential tool in data exploration and analysis, allowing a deeper understanding of underlying relationships and patterns.
Green scatter plot talking about national parks and their relationship between size and number of visitors per year
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Correlation in scatter plots
Correlation is a statistical measure of the relationship between two variables. For the purposes of this article, correlation can be observed visually through the pattern formed by the points. If the points tend to cluster in a linear or curved shape, this indicates a positive relationship between the variables. On the other hand, if the points are distributed without following any clear pattern, then they indicate a null or negative correlation.
It is important to note that a scatter plot only shows the relationship between two variables and does not necessarily imply a causal relationship. That is, a positive correlation between two variables does not necessarily mean that one causes the other.
The positive correlation
This is seen when the points exhibit an upward trend as they move from left to right on the graph. This means that as the values of one variable increase, the values of the other variable also tend to increase. This relationship indicates a direct connection between the two variables, suggesting that a change in one is generally associated with a similar change in the other.
