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Exploring Predictors for Program Retention and Success in Health Science Programs

BIO Lab Class Data for Analysis vizly more detailed.xlsx

Missing file

What predicts program retention and success?

Data Overview

The dataset contains information about students' performance in various BIO and BST courses, along with their TEAS scores. The columns include:
  • Entering Program: The program the student entered.
  • Current Program: The current program the student is in.
  • Program Status: The status of the program (1 for active, 0 for inactive).
  • BIO201 Term: Term for BIO201 course (encoded as YYMM).
  • BIO201 Grade: Grade for BIO201 course.
  • BIO201A Grade: Grade for BIO201A course.
  • BIO202 Term: Term for BIO202 course (encoded as YYMM).
  • BIO202 Grade: Grade for BIO202 course.
  • BIO202A Grade: Grade for BIO202A course.
  • BIO203 Term: Term for BIO203 course (encoded as YYMM).
  • BIO203 Grade: Grade for BIO203 course.
  • BIO203A Grade: Grade for BIO203A course.
  • BST322 Term: Term for BST322 course (encoded as YYMM).
  • BST322 Grade: Grade for BST322 course.
  • TEAS Score: TEAS score of the student.
To determine predictors for program retention and success, we will analyze the relationship between these variables and the Program Status and TEAS Score.

Correlation Analysis

The heatmap above shows the correlation between various student performance metrics. Here are some key observations:
  • Program Status has a positive correlation with grades in BIO201, BIO201A, BIO202, BIO202A, BIO203, BIO203A, and BST322 courses. This suggests that higher grades in these courses are associated with active program status.
  • TEAS Score has a positive correlation with grades in BIO201, BIO201A, BIO202, BIO202A, BIO203, BIO203A, and BST322 courses. This indicates that students who perform well in these courses tend to have higher TEAS scores.
Next, we can perform a more detailed analysis to identify specific predictors for program retention and success. Would you like to proceed with a regression analysis or any other specific analysis?

Bin the data by year and download it as an excel spreadsheet

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