Rehema Kemunto

Conducted Welch's two-sample t-test on 17,400+ hourly observations to quantify weather impact on public transit demand. Validated statistical assumptions (normality, variance) and delivered data-backed staffing recommendations achieving £23K/month cost savings through evidence-based dynamic scheduling.

Analyzed 185,000+ e-commerce transactions testing whether $X.99 pricing increases sales across product categories. Applied Mann-Whitney U test after confirming non-normal distribution via Shapiro-Wilk. Found significant effect for phones (+5.16% lift, p<0.001) but no effect for laptops, demonstrating category-specific pricing psychology.

Comprehensive MIS project tracking $66.31M revenue. Built Power BI dashboard, automated invoice alerts with Google Apps Script, and identified root cause warehouses reducing fulfillment delays through systematic data analysis.

Designed Beta-Binomial Bayesian model testing product density impact on conversion rates. Conducted sensitivity analysis across multiple priors comparing Bayesian vs Frequentist approaches. Demonstrated 98% probability of superiority and advantages of probabilistic decision-making for real-time experiments.

Analyzed 5,000+ transactions using statistical validation to diagnose 48% return rate. Identified Black variant quality issue through systematic data segmentation and delivered evidence-based recommendations projected to increase profit margin by 23%.

Full-cycle BI analysis from Power Query to strategic recommendations. Advanced DAX measures for Net Sales and Profit Margin. Delivered Q4 campaign and regional optimization strategies based on seasonal trends and profitability analysis.

Tableau dashboard using behavioral data to create distinct customer segments (High-Value, At-Risk) enabling targeted marketing campaigns and personalized retention strategies based on spending patterns and loyalty metrics.

Power BI dashboard analyzing campaigns across Facebook and Instagram. Tracked 340K impressions and $101K revenue with 333% ROI. Identified optimal ad scheduling times and demographic performance patterns for budget allocation.

Analyzed 124 years of Nobel Prize data (1,000+ laureates) to uncover trends in age, collaboration, gender representation, and geographic distribution. Built interactive Looker Studio dashboard revealing the gender gap is slowly closing (6.6% historically → 19.4% in 2020s) and solo science is extinct (78% individual prizes in early 1900s → 35% today).

Comprehensive statistical analysis using chi-square tests, ANOVA, and logistic regression to model customer satisfaction and loyalty drivers. Identified key factors influencing Net Promoter Score and likelihood to recommend.

Data analysis project using Natural Language Processing to evaluate student sentiment and satisfaction trends from campus event surveys. Applied text analysis techniques to extract meaningful insights from open-ended feedback.

Comprehensive statistical analysis exploring descriptive statistics, distribution characteristics, and relationships between key demographic variables in a dataset of 5,000 respondents. Applied correlation analysis and visualization techniques.

Applied k-means and hierarchical clustering to segment cardiovascular health data patterns from the Framingham Heart Study. Revealed distinct customer segments based on risk factors for targeted health interventions.