What is a scatter plot?

A scatter plot is a type of data visualization that displays values for typically two variables for a set of data. Each point on the scatter plot represents an observation in the dataset, with the position of the point determined by the values of the two variables being compared. ### Key Features of a Scatter Plot: 1. **Axes**: The horizontal axis (x-axis) usually represents one variable, while the vertical axis (y-axis) represents another variable. 2. **Data Points**: Each point on the plot corresponds to a single observation, with its coordinates determined by the values of the two variables. 3. **Trends**: Scatter plots can help identify relationships or correlations between the two variables. For example: - A positive correlation is indicated by points that trend upwards from left to right. - A negative correlation is indicated by points that trend downwards from left to right. - No correlation is indicated by a random distribution of points. 4. **Outliers**: Scatter plots can also reveal outliers, which are points that fall far away from the general pattern of the data. 5. **Clusters**: They can show clusters of data points, indicating groups of similar observations. ### Uses of Scatter Plots: - To visualize the relationship between two quantitative variables. - To identify trends, patterns, and correlations in data. - To detect outliers and anomalies in datasets. Overall, scatter plots are a powerful tool for exploratory data analysis and can provide insights into the nature of the relationship between variables.