Continuous Variables (Bivariate Analysis)

This module is designed to explore the relationship between two continuous variables. Use the sidebar panel to configure your inputs before navigating through the analysis tabs.

1. Select Your Variables

• Variable 1 (x): Select your independent or baseline continuous variable.
• Variable 2 (y): Select your dependent or secondary continuous variable to compare against 'x'.

2. Grouping Data

• Check the Statistics by group? box if you want to partition your bivariate analysis by a specific categorical variable.
• Once checked, select your dividing category from the group by dropdown menu.
• Note: The grouping option is only available for visual summaries. It will automatically hide if you are viewing the Dependency and Correlation Study tab.

3. Navigate the Analysis Tabs

• Use the main panel tabs to switch between the two primary analysis modes:
  • Dependency and Correlation Study: Analyze the statistical strength and direction of the relationship between your two variables (e.g., Pearson, Spearman).
  • Graphic Summary: Visualize the relationship using customized scatterplots and trend lines.

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Need to review this documentation again? Click the blue Help button in the sidebar at any time.

User Guide: Dependency and Correlation Study

The Dependency and Correlation Study tab allows you to evaluate the statistical relationship and measure the strength of association between your two selected continuous variables.

1. Select a Correlation Method

• Use the Correlation method: dropdown menu to choose the mathematical approach for calculating the relationship.
• Available options include:
  • Pearson: Best for evaluating linear relationships between normally distributed variables.
  • Spearman: A non-parametric rank correlation, useful for non-linear monotonic relationships or when outliers are present.
  • Kendall: Another non-parametric test, often preferred for smaller sample sizes or when data contains many tied ranks.
  • All: Computes and displays the results for all three methods simultaneously.

2. View the Metrics

• Once a method is selected, the application will automatically calculate the correlation coefficients and related metrics.
• The results are displayed instantly in the interactive data table directly below the dropdown menu, allowing you to easily read and export the data.

Graphic Summary (Bivariate Analysis)

The Graphic Summary tab in the bivariate module visualizes the relationship between your two selected continuous variables using an interactive Scatterplot.

1. Viewing the Scatterplot

• Once you have selected Variable 1 (x) and Variable 2 (y) in the sidebar, the scatterplot will automatically render.
• If you checked the Statistics by group? option in the sidebar, the points on the plot will be separated by color according to the categories in your grouping variable.

2. Customizing the Graph

• Click the Customize graph button (marked with a fish icon) to open the styling panel.
• Styling Options:
  • Aesthetics: Change the Theme, Font, and Font Size.
  • Point Appearance: Adjust the point Size, Shape, and Alpha (transparency).
  • Colors: If ungrouped, choose a single Color. If grouped, choose a color Palette to differentiate the categories.
  • Labels: Customize your axis titles using the xlab and ylab fields.
• Reset: Click the yellow Reset to Initial State button to quickly undo all your aesthetic changes.

3. Exporting

• When you are satisfied with how your scatterplot looks, click the blue Download Graph button to save the image to your device.