Data Analytics Projects
Experimental Design and A/B Testing
Conducted A/B testing to evaluate the impact of a new system layout on employee performance. Used a two-sample t-test to determine statistical significance. The p-value of 0.42 indicated that there was no statistically significant difference in performance between the old and new layouts.
VIEW CODEExploring Hypothesis Testing with Statistical Methods
Explore hypothesis testing with statistical methods in this project. Analyze SAT scores across school districts and sepal widths in iris flowers. Learn through visual inspection, Shapiro-Wilk tests, and skewness/kurtosis assessments. Enhance data handling and statistical analysis skills using Python libraries like Pandas, Matplotlib, and Seaborn for visualization.
VIEW CODEData Analysis Python + SQL Mini Project
Analyze household survey data to identify trends and insights. Key tasks include filtering low-income respondents, calculating average bills, and identifying households with students and extended family members. The project utilizes SQL for data management and Python for data analysis and visualization.
View CodeMySQL Clean and Exploratory Data Analysis
Cleaned duplicates, misspellings, discrepancies; analyzed states, income, outliers.
View Code