Practice Datasets
Free, curated datasets for statistical learning and practice. Each dataset includes field descriptions and direct integration with our analysis tools.
π Featured Dataset
Exam Scores Dataset
A comprehensive dataset of 100 student exam scores from multiple subjects. Perfect for learning quartile calculations, box plot creation, and outlier detection. Includes mathematics, science, and literature scores with realistic score distributions.
Field Descriptions
student_id
Unique identifier for each student (1-100)
math_score
Mathematics exam score (0-100)
science_score
Science exam score (0-100)
literature_score
Literature exam score (0-100)
Sample Data Preview
| student_id | math_score | science_score | literature_score |
|---|---|---|---|
| 1 | 85 | 92 | 78 |
| 2 | 76 | 84 | 88 |
| 3 | 94 | 89 | 91 |
| ... | ... | ... | ... |
π License & Usage
This dataset is provided for educational and learning purposes only. You are free to use, modify, and distribute this data for educational, research, or personal projects. No attribution is required, though it is appreciated. The data is synthetic and does not represent real individuals or actual exam results.
π Manufacturing & Quality Control
Factory Batch Measurements (JanβFeb 2025)
Quality control telemetry captured from a factory extrusion line. Each row represents a batch with recorded temperature, pressure, humidity, defect counts, and pass rates. Use this dataset to practice outlier detection, control chart analysis, and comparing mean vs median decisions in manufacturing environments.
Field Descriptions
BatchID
Unique batch identifier (B-001 ... B-060)
ProductionDate
Calendar date a batch was produced
Shift
Operating shift label (A/B/C)
Temperature_C
Ambient process temperature in Celsius
Pressure_PSI
Line pressure measured in PSI
Humidity_pct
Relative humidity inside production bay (%)
DefectCount
Number of units failing QA per batch
PassRate_pct
Percentage of units passing QA
Notes
Contextual engineering notes for each run
Sample Data Preview
| BatchID | Temperature_C | Pressure_PSI | DefectCount | PassRate_pct |
|---|---|---|---|---|
| B-001 | 68.5 | 112.4 | 2 | 98.0 |
| B-009 | 73.2 | 116.8 | 5 | 93.6 |
| B-057 | 74.3 | 117.9 | 6 | 92.5 |
π License & Usage
Synthetic manufacturing data released for educational and benchmarking use. Feel free to remix, annotate, and share with your teams. Attribute PlotNerd when embedding in documentation.
π° Economics & Salary Data
Salaries Distribution (Anonymized)
Anonymized salary data across 8 industries with varying experience levels, education backgrounds, and geographic locations. Perfect for understanding income distributions, analyzing salary outliers, and practicing statistical analysis on real-world economic data. Use this dataset to explore how education, experience, industry, and location affect compensation.
Field Descriptions
employee_id
Unique identifier for each employee (1-80)
industry
Industry sector (Technology, Finance, Healthcare, Education, Manufacturing, Retail, Consulting, Marketing)
experience_years
Years of professional experience (0-25)
salary_usd
Annual salary in US dollars (anonymized, realistic distribution)
location
Geographic location type (Urban, Suburban, Rural)
education_level
Highest education level (High School, Bachelor, Master, PhD)
Sample Data Preview
| employee_id | industry | experience_years | salary_usd | location | education_level |
|---|---|---|---|---|---|
| 1 | Technology | 5 | 95000 | Urban | Master |
| 2 | Finance | 12 | 125000 | Suburban | Bachelor |
| 3 | Healthcare | 3 | 72000 | Urban | Bachelor |
| ... | ... | ... | ... | ... | ... |
π License & Usage
This dataset contains completely synthetic and anonymized salary data generated for educational purposes only. All values are fictional and do not represent real individuals, companies, or actual salary data. Free to use for educational, research, or personal projects. No attribution required, though it is appreciated.
π Coming Soon
E-commerce Order Amounts
Transaction amounts from online retail. Great for business analytics and customer behavior analysis.
π Usage Guidelines
π License & Usage
- β Free for educational and learning purposes
- β Use in academic research and coursework
- β Practice statistical analysis techniques
- β Commercial use without attribution
π How to Use
- 1. Download the CSV file to your computer
- 2. Use "Open in Tool" buttons for direct analysis
- 3. Copy specific columns for focused analysis
- 4. Reference field descriptions for context