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) represents one variable, while the vertical axis (y-axis) represents the other 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 reveal relationships between the two variables, such as: - Positive correlation: As one variable increases, the other variable also increases. - Negative correlation: As one variable increases, the other variable decreases. - No correlation: There is no apparent relationship between the two variables. 4. **Outliers**: Scatter plots can help identify outliers, which are points that fall far away from the general pattern of the data. 5. **Clusters**: They can also 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, correlations, and patterns in data. - To detect outliers and anomalies in the dataset. Overall, scatter plots are a powerful tool for exploratory data analysis and can provide insights into the nature of the relationship between variables.