LaurenObioha/Impact-Evaluation-Analysis-of-EQUIP-Tanzania-Program-using-R

# Impact-Evaluation-Analysis-of-EQUIP-Tanzania-Program # 📋 Overview The project measures the impact of Educational Quality Improvement Programme (EQUIP) in Tanzania on pupil learning. Using statistical hypothesis testing, the analysis determines if the pupil learning significantly improved. # 📌 Objective The objective is to determine if the EQUIP programme statistically affects pupil learning in Tanzania. # 📈 Analysis Workflow - Imported and three inspected datasets from the World Bank: `EQUIP_BL`: The baseline survey,`EQUIP_ML`: the midline survey, `EQUIP_BLML`: the combined baseline- and midline-survey. - Conducted randomization test. - Conducted randomized control trial test. - Conducted Endogenity tests. - Conducted a Two-sample t-test. - Conducted Propensity score matching and Difference in Difference Method - Conducted regression analysis and computed summary statisctics. - Interpreted statistical results. - Reported findings and conclusions. # 🔍 Example Result - Null hypothesis (H0): The true difference in means between group 0 and group 1 is equal to 0 - Alternative hypothesis (H1): The true difference in means between group 0 and group 1 is not equal to 0 After performing two-sample t-test: - p-value Reject H0 - Conclusion: The EQUIP-Tanzania programme has no statistically significant impact on the pupil’s reading comprehension suggesting that the pupil's learning is not significantly improved. # 💡 Key Learnings - Applying hypothesis testing to real-world data. - Understanding how sample means compare to population benchmarks. - Communicating findings through staistical reasoning and visuals. - Reproducible workflows for academic-style data analysis.