Being Intentional: AB Testing and Data Minimization - PEPR '24
Explore data minimization techniques for AB testing, focusing on statistical approaches that don't require linking to individual customer IDs, promoting privacy-conscious analytics practices.
Data Analysis in Python - From Descriptive Statistics to Advanced Analytics
Master data analysis fundamentals in Python, from environment setup and data cleaning to advanced statistical methods like T-tests, ANOVA, and regression, with practical business applications and visualization techniques.
Bivariate Analysis in R
Learn bivariate analysis techniques in R, including t-tests, ANOVA, chi-square, correlations, and linear regression. Gain practical skills for data science and statistics using RStudio.
R Tutorials
Comprehensive R tutorials covering data management, analysis, and visualization, with hands-on exercises using real datasets and practical applications in statistics and data science.
Power & Sample Size in R
Learn to calculate power and sample size for various statistical tests in R, from t-tests to ANOVA and multivariate analyses, enhancing your ability to design robust studies.
Oneway ANOVA
Explore variation splitting using ANOVA, covering model specification, ANOVA tables, and practical applications in food science data analysis.