What is a scatter plot?

A **scatter plot** is a type of data visualization that displays values for two different variables for a set of data. Each individual data point is represented as a dot on a two-dimensional graph, where: - **X-axis (horizontal)** represents one variable. - **Y-axis (vertical)** represents the other variable. **Purpose of a Scatter Plot:** 1. **Identify Relationships:** Scatter plots are primarily used to determine if there's a relationship or correlation between the two variables. For example, they can show whether an increase in one variable tends to be associated with an increase or decrease in the other. 2. **Detect Patterns and Trends:** They help in spotting trends, clusters, or patterns within the data. This can be useful in fields like economics, biology, engineering, and social sciences. 3. **Highlight Outliers:** Scatter plots can reveal outliers or anomalies in the data that may require further investigation. **Example:** Imagine you're analyzing the relationship between hours studied and exam scores for a group of students. - **X-axis:** Number of hours studied. - **Y-axis:** Exam score. Each point on the scatter plot represents a student’s hours studied and their corresponding exam score. If the points trend upward from left to right, it may suggest that more study hours are associated with higher exam scores. **Adding a Trend Line:** Often, a trend line (also known as a line of best fit) is added to a scatter plot to summarize the overall direction of the data points. This line can help in understanding the strength and nature (positive, negative, or no correlation) of the relationship between the variables. **Benefits:** - **Visual Clarity:** Provides a clear visual representation of data relationships. - **Simplicity:** Easy to create and interpret, making it accessible for various audiences. - **Analytical Insight:** Aids in making informed decisions based on data trends and correlations. Overall, scatter plots are powerful tools in data analysis for exploring and illustrating the potential connections between two quantitative variables.