A scatter plot is a type of mathematical diagram using Cartesian coordinates to display values for two variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis.

To create a scatter plot, follow these steps:

- Identify the variables to be plotted on the x-axis and y-axis.
- Label the x-axis and y-axis with the appropriate variable names.
- Plot each data point with the x-value on the horizontal axis and the y-value on the vertical axis.
- Once all points are plotted, analyze the pattern of the points to determine if there is a relationship between the variables.

When interpreting a scatter plot, look for the following patterns and relationships:

- Positive Correlation: When the points on the scatter plot form a pattern that slopes upwards from left to right, it indicates a positive correlation between the variables.
- Negative Correlation: When the points on the scatter plot form a pattern that slopes downwards from left to right, it indicates a negative correlation between the variables.
- No Correlation: When the points on the scatter plot do not form a clear pattern or trend, it indicates no correlation between the variables.
- Strength of Correlation: The closer the points are to forming a straight line, the stronger the correlation between the variables.

Scatter plots are useful for analyzing and visualizing relationships between two variables. They can help identify correlations, trends, clusters, and outliers within a dataset.

- What is a scatter plot and how is it created?
- How do you interpret the patterns in a scatter plot?
- What are the different types of correlations that can be identified in a scatter plot?
- How can scatter plots be used for data analysis and visualization?

By understanding the concepts and principles of scatter plots, you can effectively analyze and interpret relationships between variables in a dataset.

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Data Analysis and Probability (NCTM)

Formulate questions that can be addressed with data and collect, organize, and display relevant data to answer them.

Select, create, and use appropriate graphical representations of data, including histograms, box plots, and scatterplots.

Select and use appropriate statistical methods to analyze data.

Discuss and understand the correspondence between data sets and their graphical representations, especially histograms, stem-and-leaf plots, box plots, and scatterplots.