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Student Study Hours and Marks
Education & Learning Analytics
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About
This dataset provides a clear relationship between the number of hours a student has studied and the academic marks they achieved. It is ideal for exploring basic linear regression models and understanding the direct impact of study effort on educational outcomes.
Columns
- Hours: Represents the number of hours a student dedicated to studying.
- Minimum Value: 1.10 hours
- Maximum Value: 9.20 hours
- Average Value (Mean): 5.01 hours
- Standard Deviation: 2.47 hours
- Total Records: 25
- Scores: Represents the marks obtained by the student.
- Minimum Value: 17 marks
- Maximum Value: 95 marks
- Average Value (Mean): 51.5 marks
- Standard Deviation: 24.8 marks
- Total Records: 25
Distribution
The dataset is provided in a CSV format and is relatively small, with a file size of 187 bytes. It contains two distinct columns and 25 records, with no missing or mismatched entries for either column, ensuring data completeness.
Usage
This dataset is particularly well-suited for:
- Applying simple linear regression to predict student marks based on study hours.
- Educational research analysing the correlation between effort and academic performance.
- Introductory data analytics projects for beginners.
- Demonstrating predictive modelling in an educational context.
Coverage
The dataset focuses exclusively on student study hours and their corresponding academic marks. No specific geographic locations, time ranges, or demographic details about the students are provided within the dataset.
License
CC0: Public Domain
Who Can Use It
This dataset is beneficial for a wide range of users, including:
- Students and educators: For learning and teaching about data analysis, statistics, and linear regression.
- Beginner data scientists: To practice their skills on a straightforward, clean dataset.
- Academics and researchers: To explore fundamental relationships in educational data.
- Anyone interested in basic predictive modelling: To understand how to forecast outcomes from a single input variable.
Dataset Name Suggestions
- Student Study Hours and Marks
- Academic Performance Predictor
- Study Time vs. Scores
- Student Success Factors
Attributes
Original Data Source: Student Study Hours and Marks
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