This is a collection of my lecture notes designed to enhance learning and solidify my understanding of essential probability and statistics concepts crucial for mastering Machine Learning and Data Science.

Applied Statistics

Experimental Design

This lecture note contains a summary of what I have learned about experimental design, also known as design of experiments (DOE). Here are some disclaimers:

• The contents of this note are based on the following courses:
  • STAT-5303 Experimental Designs offered by Oklahoma State University.
  • Design of Experiments Specialization offered by Arizona State University, hosted by Coursera.
• The contents of this note are also based on the following books:
  • Dean, Voss, Draguljić (2017). Design and Analysis of Experiments (2nd Edition).
  • Kuehl (2000). Design of Experiments - Statistical Principles of Research Design and Analysis (2nd Edition).
  • Montgomery (2017). Design and Analysis of Experiments (9th Edition).

Time Series Analysis

This lecture note contains a summary of what I have learned about the topic of time series, which is an advanced subject in probability and statistics. Here are some disclaimers:

• The contents of this note are based on the following courses:
  • STAT-5053 Time Series Analysis offered by Oklahoma State University.
• The following textbooks is used to complement this lecture note.
  • Cryer, Chan (2008). Time Series Analysis with Applications in R (2nd Edition).
  • Montgomery, Jennings, Kulahci (2015). Introduction to Time Series Analysis and Forecasting (2nd Edition).