Fundamentals of Computational Statistics provides participants with essential tools and methodologies for analyzing and interpreting data through computational techniques. The course emphasizes hands-on learning, enabling students to engage with real-world datasets and apply statistical methods to derive meaningful insights. Participants will gain proficiency in various computational tools and statistical software, equipping them to tackle complex data challenges in diverse professional settings.
Throughout the program, learners will explore a range of topics that bridge theoretical knowledge and practical application. The course is structured to foster collaboration and innovation, culminating in a final project where students will present their findings, with opportunities for publication in Cademix Magazine. This course is designed for those looking to enhance their analytical skills and advance their careers in data-driven fields.
Introduction to Statistical Concepts and Terminology
Overview of Computational Statistics and Its Applications
Data Collection Techniques and Data Management
Exploratory Data Analysis (EDA) Methods
Probability Distributions and Statistical Inference
Hypothesis Testing and Confidence Intervals
Regression Analysis and Model Fitting
Introduction to Machine Learning Algorithms
Data Visualization Techniques and Tools
Final Project: Application of Computational Statistics to a Real-World Dataset