Scatter Matrix Example

Scatter Matrix Example

Problem Statement

The data shown in the data tab contains info on adv spend vs. sales revenue. Create a scatter plot between the two variables and draw any conclusions from this exercise. 

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 Scatter Matrix.


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. Scatter Plot Overview

  • The scatter plot displays the relationship between Ads (X-axis) and Sales (Y-axis).
  • Two groups of data points are plotted, each represented with different colors.

2. Best Fit Line

  • Two linear trendlines (one for each group) suggest a positive correlation between ad spending and sales.
  • The slope of the lines indicates that as the number of ads increases, sales tend to rise.

3. Data Summary

  • Total Data Rows: 13
  • Groups: 2 distinct sets of observations are analyzed separately.

4. Group 1 Analysis

  • N (Sample Size): 6 observations
  • Ads Range: 30 to 50
  • Sales Range: 700 to 850
  • Mean Ads Spend: 37.67
  • Mean Sales: 758.33
  • Standard Deviation (Ads): 8.26
  • Standard Deviation (Sales): 57.07

5. Group 2 Analysis

  • N (Sample Size): 7 observations
  • Ads Range: 25 to 52
  • Sales Range: 721 to 920
  • Mean Ads Spend: 41.29
  • Mean Sales: 812.43
  • Standard Deviation (Ads): 12.11
  • Standard Deviation (Sales): 78.85

6. Variability in Data

  • Group 2 shows more variability in both ads spend and sales (higher standard deviation).
  • Group 1 has a more consistent pattern with a smaller range and deviation.

7. Strength of Relationship

  • The presence of a linear trendline suggests that sales are influenced by ad spend.
  • A stronger correlation would be indicated if the data points were more tightly clustered around the trendline.

8. Comparative Performance of Groups

  • Group 2 has higher mean sales (812.43) than Group 1 (758.33), despite similar ad spend.
  • This could indicate that factors beyond ads (e.g., product quality, market conditions) influence sales.

9. Conclusion from Analysis

  • Sales increase with ad spend, but not perfectly linearly.
  • The correlation is positive, meaning higher ad spend generally results in higher sales, but with some variation.
  • Group 2 appears to have better returns on ad spend than Group 1.

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