Cohort Analysis
Students with 2+ consecutive years at your school outperform transfers. Prove it with statistically rigorous data.
What is Cohort Analysis?
Charter school authorizers often ask: "Is your school actually improving outcomes, or just attracting higher-performing students?"
Cohort Students
Students with 2+ consecutive years at your school with gaps of ≤180 days between enrollments.
Non-Cohort Students
Students who transferred in recently or had significant gaps in enrollment.
Gap Tolerance
Allows for summer breaks while excluding long transfers
Statistically Rigorous Methods
Research-accepted methods that authorizers and evaluators trust.
Cohen's d Effect Size
Measures the magnitude of difference between cohort and non-cohort groups in standardized units.
Cohen's d Effect Size
Mann-Whitney U Test
A non-parametric test that determines whether the difference between groups is statistically significant.
Why non-parametric? Educational data often isn't normally distributed. Mann-Whitney U is robust to skewed distributions and outliers.
Authorizer-Ready Reports
Reports designed for authorizer presentations and board meetings.
Interpretation
Cohort students show a medium-to-large effect size advantage (d = 0.62) in growth over non-cohort peers. This difference is highly statistically significant (p < 0.01), indicating the school's program adds measurable value for students who remain enrolled for 2+ years.
When to Use Cohort Analysis
Charter Reauthorization
Present defensible evidence of your school's value-add to authorizers during renewal reviews.
Board Reporting
Give your board statistically rigorous data on program effectiveness, not just anecdotes.
Grant Applications
Demonstrate measurable impact when applying for competitive education grants.
Program Evaluation
Compare cohort performance across different programs, campuses, or grade bands.
Ready to Prove Your School's Value-Add?
See how cohort analysis can help you demonstrate impact to your authorizer, board, and community.



