Auda: Variables Continuas (Bivariadas)

## 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.

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.