Data Visualization with Jamovi
ImportantNote
We use the Jamovi Desktop version 2.7.3 (released on July 31, 2025). Click here to download the lastest version
Click here to download every dataset from GOOGLE DRIVE
Every graph on the page is created using R; some graphs cannot be created in Jamovi.
A histogram is used to show the distribution of a single numeric variable. It helps us understand how data are spread, whether they are skewed, symmetric, or bimodal, and allows us to identify patterns, outliers, or frequencies within specified intervals (called bins).
Business Scenario: Monthly Sales Analysis of a Retail Store
A retail chain wants to understand the distribution of monthly sales revenue across its 100 store branches. The business team wants to know whether most stores are underperforming, average, or generating high revenue, in order to design appropriate incentive plans.
Use branch_monthly_sales.csv
NoteQuestions:
What is the distribution of monthly sales revenue among the branches?
Are most branches generating low, average, or high revenue?
Is the distribution symmetric or skewed?
CautionA distribution is symmetric or skewed, you can look at the shape of the histogram:
How to Check from a Histogram
Symmetric Distribution
The histogram looks like a mirror image on both sides of the center (like a bell shape).
The left and right sides are roughly equal in height and spread.
Example: Normal distribution.
Right-Skewed (Positively Skewed)
The tail is longer on the right (toward higher values).
Most data are concentrated on the left.
Common in income, prices, or waiting times.
Left-Skewed (Negatively Skewed)
The tail is longer on the left (toward lower values).
Most data are concentrated on the right.
Common in age at retirement or test scores with high averages.
Tips:
Focus on the center, spread, and tails of the bars.
If the peak is off-center and the bars stretch more on one side, it’s skewed.
Use mean vs. median as a cross-check:
If mean ≈ median → symmetric
If mean > median → right-skewed
If mean < median → left-skewed
๊Use histogram.csv
Results from Jamovi
To explore this dataset, open branch_monthly_sales.omv in Jamovi.
Regional Sales Comparison
A company operates in two major regions: North and South. Management wants to compare the monthly sales distribution of branches in each region.
Use regional_sales_data.csv
Results from Jamovi
To explore this dataset, open regional_sales_data.omv in Jamovi.
A bar plot is a graphical representation used to display and compare the values of categorical data. Each bar represents a category, and the height (or length) of the bar reflects its frequency, count, or another summary statistic. Bar plots are ideal for visualizing differences across discrete groups, such as sales by region or product types.
Or the bar plot is used to display the relationship between a categorical variable and a numerical variable. Each bar represents a category (e.g., product name), and its height (or length) shows the corresponding value (e.g., total sales). Bar plots are useful for comparing quantities across categories and identifying trends or differences among groups.
Average Monthly Revenue by Product Category
A company sells four types of products: Laptops, Tablets, Phones, and Accessories. Management wants to compare the average monthly revenue generated by each product category in order to prioritize marketing and inventory strategies.
Use product_revenue_data.csv
| Product | Average_Revenue |
|---|---|
| Laptop | 1307.3902 |
| Phone | 1006.3857 |
| Tablet | 801.5192 |
| Accessory | 193.5946 |
Extra
Average revenue by salesperson
Revenue comparison by product and salesperson (grouped bar plot or facet)
Grouped Bar Plot (Bar plot with fill = Salesperson)
Facet Bar Plot (Facet by Salesperson)
Jamovi allows you to generate bar plots based on the mean of a numeric variable or the frequency of a categorical variable.
To explore this dataset, open product_revenue_data.omv in Jamovi.
If you need the bar plot of total value, you can use PivotTable in Excel and select pivot chart.
A scatter plot is a graphical tool used to display the relationship between two numerical variables. Each point on the plot represents an observation with coordinates defined by the values of the two variables. Scatter plots help identify patterns such as linear or nonlinear trends, clusters, and potential outliers. They are commonly used to explore correlations and assess the strength and direction of relationships between variables.
Analyzing Relationships Between Business Metrics
A business analyst wants to explore the relationships between different variables collected from 100 retail stores. The goal is to determine which metrics are linearly related, which show nonlinear patterns, and which show no correlation at all.
Use business_metrics_data.csv
Scatter Plots to Visualize the Relationships
Advertising_Spend vs. Revenue: Strong linear positive correlation
Customer_Satisfaction vs. Return_Rate: Nonlinear (inverted-U shape) relationship
Store_Size vs. Delivery_Speed: No clear correlation
Business Questions
Which pair of variables shows a strong linear relationship?
Which pair appears to be nonlinearly related?
Which variables appear to have no correlation at all?
Based on the relationships, which variables could be used for predictive modeling?
What kind of transformation (if any) might help in modeling nonlinear relationships?
To explore this dataset, open business_metrics_data.omv in Jamovi.
A line chart is used to show trends or changes over time. It connects data points with lines to highlight patterns, such as increases or decreases in values. Line charts are ideal for tracking metrics like monthly sales, stock prices, or website traffic.
Business Cases
A company wants to track and compare the monthly sales performance of its three sales representatives — Alice, Bob, and Charlie — over a two-year period. The sales team and management aim to identify trends, seasonal patterns, and overall performance to support strategic planning and incentive programs.
To visualize this, a line chart is created to show how each salesperson’s revenue changes from month to month between 2023 and 2024.
Use sales_data_month.csv
❓ Key Questions for Analysis:
Who shows the most consistent sales performance over time? (Look for steady lines with little fluctuation.)
Are there any noticeable trends or seasonal patterns? (E.g., Does revenue always peak in certain months like December?)
Which salesperson had the highest overall growth in sales over the two years?
Did any salesperson experience a significant drop in sales? If so, when?
How do the sales levels of each person compare month by month? (Use this to identify who leads or lags during specific periods.)
To explore this dataset, open sales_data_month.omv in Jamovi.
How to Install Extra Modules in Jamovi
Step 0: Launch Jamovi
Step 1: Click on the Modules icon in the top-right corner
Step 2: Click on the jamovi library
We recommend the following Jamovi libraries:
surveymv – for visualizing survey data
OneHotEncoding – for categorical data transformation
vijPlots – for advanced data visualization
distrACTION – for learning and exploring statistical distributions
Step 3: Search for the desired library and click Install
