Scatter plot overview

Scatter plot overview

A scatter plot is a graph representing the relationship between two variables. It is a graph with points plotted on a Cartesian coordinate system, where each point represents an observation in the dataset. The x-axis typically represents the independent variable, while the y-axis represents the dependent variable. The key features are:
  1. Points: Each data point represents values (x, y).
  2. Trends: It helps visualize patterns, trends, and relationships.
  3. Clusters/Outliers: It can identify clusters of data and outliers.
Types of Correlations
  1. Positive Correlation: As x increases, y also increases.
  2. Negative Correlation: As x increases, y decreases.
  3. No Correlation: No apparent relationship between x and y.
Application
Description
Relationship Analysis
It helps to find out whether there is a relationship (correlation) between two variables. For instance, a scatter plot of study hours (x) vs. exam scores (y) may indicate a positive relationship.
Trend Identification
Patterns like linear, non-linear, or no correlation can be identified. It helps determine whether the relationship is increasing, decreasing, or trending
Identification of Outliers
It is easy to identify points that considerably deviate from the overall pattern.
Regression Analysis
Used as a precursor to fit regression lines or curves to understand the mathematical relationship.
Comparative Analysis
It is commonly used to compare the relationship between variables across categories.

Reference: Some of the text in this article has been generated using AI tools such as ChatGPT and edited for content and accuracy.

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