Statistics III(Advanced and Applied Statistics)

Statistics III focuses on advanced statistical methods, multidimensional data analysis, and integration with AI and data science. You’ll work with ANOVA, nonparametric methods, categorical modelling, time series, multivariate techniques, Bayesian inference, and modern resampling strategies. The course concludes with applications in statistical machine learning and hands-on capstone projects using real-world datasets.

What you’ll learn

  • Apply one-way, two-way ANOVA and post hoc testing with diagnostic checks.
  • Use nonparametric techniques for non-normal and ordinal data.
  • Model categorical outcomes using logistic regression and interpret odds ratios.
  • Analyze time series data for trends, seasonality, and forecasting with ARIMA basics.
  • Perform multivariate analysis including PCA, factor analysis, and clustering.
  • Understand Bayesian principles and apply them to inference problems.
  • Implement resampling methods such as bootstrapping and jackknife.
  • Integrate statistical concepts into AI models for feature selection and prediction.
  • Complete capstone projects with real-world datasets and full statistical workflows.