Lectures related to R (programming language)

Introduction to R Programming for Genetics & Genomics

Introduces a course on Genetics & Genomics, focusing on R programming with interactive exercises.

R Programming: Conditions, Loops, Functions & Graphics

Covers conditions, loops, functions, and graphics in R programming with practical examples.

Continuous-Time Stochastic Processes: Linear System

Covers the analysis of continuous-time stochastic processes in the context of linear systems.

Model Formulas in R: Basics and Applications

Explores model formulas in R, covering basics, interactions, ANOVA, and factorial designs with practical examples.

Binomial Distribution in R

Introduces the Binomial distribution in R with examples of n coin tosses.

ANOVA & Moderation

Covers ANOVA, mediation, and moderation analyses in R for CS-411 Digital Education.

Algorithmic Composition: Semester Project Milestones

Covers semester project milestones in Algorithmic Composition, exploring musical concepts, technical tools, and final deliverables.

Interatomic Potentials: LJ and EAM

Explores LJ and EAM interatomic potentials, fitting to material properties and challenges in empirical potential fitting.

Reproducible Research: Principles and Tools

Covers the principles and tools for reproducible research in biostatistics, emphasizing the importance of complete documentation and the use of text editors for compiling source documents.

Exploratory Data Analysis: Binning and Histograms

Covers statistical frequency, binning, histograms, and R data analysis basics.

Defects in Crystals: Point Defects and Dislocations

Explores point defects and dislocations in crystals, highlighting their impact on material properties and the importance of energy relaxation.

Model-Based Clustering Methods

Introduces model-based clustering methods using mixture models and latent variables, with practical examples on iris data.

Matlab: Interactive Mode and Project Steps

Introduces Matlab basics, error handling, and billiards project concepts.

Comparing Convergence of Improper Integrals

Explores the comparison of convergence of improper integrals and the importance of analyzing functions for convergence.

Experimental Research Design: T-Test Analysis

Explores digital lesson development, experimental research, t-tests, ANOVA, and statistical analysis using R.

Python Programming Basics

Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.

Boolean Types and Control Structures

Explores boolean types, logical operators, and control structures in Python, emphasizing the evaluation of expressions and the use of relational operators.

Monetary Policy and Public Debt Analysis

Analyzes monetary and fiscal policy responses to public debt accumulation and the impact of Covid-19 on global economies.

Linear Regression: Confidence Bounds

Covers linear regression coefficients, confidence intervals, and R's calculation methods.

Recursive Functions: Examples and Applications

Explores recursive functions, including factorials and Fibonacci sequences, and their scope and namespaces.