# Jamovi Data Exploration (Scatter Plot)

![](https://cdn-images-1.medium.com/max/1000/0*XBcYZT7HXsGTiF55.png align="left")

The screenshot displays the **Scatter Plot** module under the **Exploration** group in **jamovi**, a statistical software environment designed for visual data exploration.

In the left panel, variable assignments are configured:

* The variable **Hours\_Studied** is placed in the **X-Axis** field, indicating it serves as the horizontal axis variable.
    
* The variable **Exam\_Score** is placed in the **Y-Axis** field, indicating it serves as the vertical axis variable.
    
* The **Grouping Variable** field remains empty, meaning no categorical variable is used to differentiate data points by color or shape.
    

Below these fields, collapsible sections labeled *General Options*, *Plot & Axis Titles*, *Axes*, and *Legend* are visible. These sections allow customization of plot appearance, including titles, axis scales, and legend formatting.

In the right panel, under the **Results** heading, the generated scatter plot is displayed. Each point represents an individual observation plotted according to its values for *Hours\_Studied* (x-axis) and *Exam\_Score* (y-axis). The pattern of points suggests a positive association: higher study hours generally correspond with higher exam scores. The relationship appears approximately linear, without obvious outliers or clusters.

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A **grouping variable** is a categorical variable used to partition data into distinct subsets for comparative visualization or analysis.

* Use grouping **after** inspecting the overall (ungrouped) scatter plot — to avoid premature focus on subgroup noise.
    
* Pair grouped scatter plots with **separate correlation coefficients or regression lines per group** (enabled via *Add regression line* and *Grouped* options in jamovi’s *General Options*).
    
* Ensure the grouping variable is correctly set as **nominal** or **ordinal** in the data spreadsheet (indicated by the “A” icon in jamovi), not continuous.