Marginal Plot Example

Marginal Plot Example

Problem Statement

Create a marginal plot for Cars data shown in the data tab. The variables of interest are Y axis (disp) and X axis (cyl). Data is attached is attachment.

How to perform analysis

Step 1: Open Sigma Magic
  1. Click on the Sigma Magic button on the Excel toolbar.
  2. Click on the New button to create a new project.
Step 2: Add the analysis template
  1. Click on the Tool Wizard to add the analysis template.
  2. Click on Analytics and then Marginal Plot.


Step 3: Specify analysis options
A new worksheet will be added to your workbook. Analysis Setup will be automatically opened, in the setup tab specify the survey results.



Click on Data to specify the data required for this analysis.



If you need to make changes to the charts, specify the optional settings in the Charts tab.

 Labels:

  • Add a title for the chart.
  • Label the X-axis and Y-axis appropriately.

Appearance:

  • Adjust colors, font sizes, or other visual elements as needed.
  • Enable/disable gridlines or background shading.


Click the Verify tab to ensure all the inputs are okay and shown in a green checkmark.



Step 4: Generate analysis result
Click OK and then click Compute Outputs to get the final results.



Interpretation of Results

  1. The analysis is conducted on continuous variables, specifically "gear" and "carb" from Table1.
  2. The marginal plot uses boxplots to represent data distributions along the x-axis (carb) and y-axis (gear).
  3. The boxplots indicate how the data is spread. If the boxes are narrow, the data is concentrated around the median. Wider boxes suggest higher variability.
  4. Any points outside the whiskers of the boxplots could indicate outliers in the dataset. These need further investigation.
  5. The scatter plot in the center suggests whether there is a correlation between gear and carb. If there is no visible trend, the relationship might be weak or non-existent.
  6. The boxplots show medians, interquartile ranges (IQRs), and overall spread. If the median is closer to one side of the box, it indicates skewness.
  7. The margin size is set to Auto, meaning the software adjusts the width of the boxplots dynamically based on data density.
  8. If the boxplots are symmetrical, the data is normally distributed. If they are skewed (one whisker is significantly longer), the data may not be normally distributed.
  9. The message confirms that the marginal plot has been successfully generated and reflects the dataset characteristics.
  10. The marginal plot provides insights into the individual distributions of gear and carb, helps detect any anomalies or trends, and visually represents potential relationships between the two variables.

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