Exploring Correlations Between Student Grades and Attendance

Apr 2, 2024, 9:12 AM

Are there any correlations between student grades and attendance?

Continue the analysis

The provided Excel file contains a single sheet named STF302BCH23, which appears to include data related to YABA COLLEGE OF TECHNOLOGY, specifically for the course STF302 LABORATORY MGT/GLASS BLOWING. The initial rows contain header and title information, with the following columns identified:
  • Matricno: Likely the student's matriculation number or ID.
  • CA_BY40: Possibly continuous assessment scores out of 40.
  • EXAM_BY100): Likely exam scores out of 100, though there seems to be a typo in the column name.
  • EXAM_BY60: Another column for exam scores, possibly out of 60.
  • TOTAL: Likely the total score for the course.
To analyze the correlation between grades and attendance, we need to identify which columns represent grades and if any column explicitly represents attendance. The provided preview does not show an attendance column, so further inspection of the dataset is needed to locate this information, if available.

Visualize this for me

We've successfully cleaned and prepared the dataset from the STF302BCH23 sheet, which contains student scores for a course at YABA COLLEGE OF TECHNOLOGY. The data includes:
  • Matricno: Student's matriculation number or ID.
  • CA out of 40: Continuous assessment scores out of 40.
  • EXAM out of 100: Exam scores out of 100.
  • EXAM out of 60: Another column for exam scores, possibly adjusted, out of 60.
  • TOTAL: The total score for the course.
Next, we will visualize the relationships between the continuous assessment scores, exam scores, and total scores to explore potential correlations.
We've successfully cleaned and analyzed the dataset from the STF302BCH23 sheet, containing student scores for a course at YABA COLLEGE OF TECHNOLOGY. Here's what was done:
  • Data Cleaning: Corrected column names and converted scores to numeric types for analysis.
  • Visualization: Created a scatter matrix to explore the relationships between Continuous Assessment scores, Exam scores, and Total scores.
Findings:
  • The scatter matrix visualizes the relationships between different types of scores. While the graph itself is not displayed in this summary, it typically shows how each type of score correlates with the others, potentially indicating patterns such as higher continuous assessment scores leading to higher total scores.
This analysis helps in understanding how different components of students' grades relate to each other, though it does not directly address the correlation between grades and attendance due to the absence of attendance data.

test this null hypothesis, every student with a CA score less than 20 had a total score of less than 50

We tested the null hypothesis that every student with a CA score less than 20 had a total score of less than 50. The results from the one-sample t-test are:
  • T-statistic: -3.4701011325530033
  • P-value: 0.0009514138514280417
Interpretation:
Given the p-value is less than 0.05, we reject the null hypothesis. This suggests that not all students with a CA score less than 20 have a total score of less than 50. There is statistically significant evidence that some students with CA scores less than 20 have total scores greater than 50.

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